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paper_id stringlengths 19 21	paper_title stringlengths 8 170	paper_abstract stringlengths 8 5.01k	paper_acceptance stringclasses 18 values	meta_review stringlengths 29 10k	label stringclasses 3 values	review_ids list	review_writers list	review_contents list	review_ratings list	review_confidences list	review_reply_tos list
iclr_2018_H1a37GWCZ	UNSUPERVISED SENTENCE EMBEDDING USING DOCUMENT STRUCTURE-BASED CONTEXT	We present a new unsupervised method for learning general-purpose sentence embeddings. Unlike existing methods which rely on local contexts, such as words inside the sentence or immediately neighboring sentences, our method selects, for each target sentence, influential sentences in the entire documen...	rejected-papers	The paper presents an interesting extension of the SkipThought idea by modeling sentence embeddings using several document-structure related information. Out of the various kinds of evaluations presented, the coreference results are interesting -- but, they fall short by a bit (as noted by Reviewer 2) because they don...	train	[ "HJUoksOxG", "HkMKdz9gz", "BkJBMfslf", "SkhSHOa7z", "Sk9XSOaXf", "BkN-ruaXf", "r17sEOTmz", "ryrYVu6XM", "HJU4pLHzM", "B1mXQXi-M" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer" ]	[ "This paper presents simple but useful ideas for improving sentence embedding by drawing from more context. The authors build on the skip thought model where a sentence is predicted conditioned on the previous sentence; they posit that one can obtain more information about a sentence from other \"governing\" senten...	[ 7, 5, 5, -1, -1, -1, -1, -1, -1, -1 ]	[ 4, 4, 4, -1, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_H1a37GWCZ", "iclr_2018_H1a37GWCZ", "iclr_2018_H1a37GWCZ", "B1mXQXi-M", "B1mXQXi-M", "B1mXQXi-M", "HkMKdz9gz", "HJUoksOxG", "B1mXQXi-M", "BkJBMfslf" ]
iclr_2018_Sk03Yi10Z	An Ensemble of Retrieval-Based and Generation-Based Human-Computer Conversation Systems.	Human-computer conversation systems have attracted much attention in Natural Language Processing. Conversation systems can be roughly divided into two categories: retrieval-based and generation-based systems. Retrieval systems search a user-issued utterance (namely a query) in a large conversational repository and retu...	rejected-papers	This paper presents an ensemble method for conversation systems, where a retrieval-based system is ensembled with a generation-based system. The combination is done via a reranker. Evaluation is done on one dataset containing query reply pairs with both BLEU and human evalutations. The experimental results are good ...	train	[ "SksrEW9eG", "rkQ2C8cxz", "S1EhNw2gz" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "Summary:\n\nThe paper proposes a new dialog model combining both retrieval-based and generation-based modules. Answers are produced in three phases: a retrieval-based model extracts candidate answers; a generator model, conditioned on retrieved answers, produces an additional candidate; a reranker outputs the best...	[ 5, 5, 6 ]	[ 3, 3, 3 ]	[ "iclr_2018_Sk03Yi10Z", "iclr_2018_Sk03Yi10Z", "iclr_2018_Sk03Yi10Z" ]
iclr_2018_rkaqxm-0b	Neural Compositional Denotational Semantics for Question Answering	Answering compositional questions requiring multi-step reasoning is challenging for current models. We introduce an end-to-end differentiable model for interpreting questions, which is inspired by formal approaches to semantics. Each span of text is represented by a denotation in a knowledge graph, together with a vect...	rejected-papers	This paper presents a neural compositional model for visual question answering. The overall idea may be exciting but the committee agrees with the evaluation of Reviewer 1: the experimental section is a bit thin and it only evaluates against an artificial dataset for visual QA that does not really need a knowledge ba...	train	[ "B1uoZsYlM", "SyvmULHVf", "BJ-RO0meG", "ryx2q7_eG", "S1J7L_TQf", "rJsg8_TXf", "HkBCBuamf", "H1qKB_6Xf" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "The paper describes an end to end differentiable model to answer questions based on a knowledge base. They learn the composition modules which combine representations for parts of the question to generate a representation of the whole question. \n\nMy major complaint is the evaluation on a synthetically generate...	[ 4, -1, 5, 7, -1, -1, -1, -1 ]	[ 4, -1, 4, 4, -1, -1, -1, -1 ]	[ "iclr_2018_rkaqxm-0b", "H1qKB_6Xf", "iclr_2018_rkaqxm-0b", "iclr_2018_rkaqxm-0b", "iclr_2018_rkaqxm-0b", "B1uoZsYlM", "ryx2q7_eG", "BJ-RO0meG" ]
iclr_2018_r1kNDlbCb	Learning to Encode Text as Human-Readable Summaries using Generative Adversarial Networks	Auto-encoders compress input data into a latent-space representation and reconstruct the original data from the representation. This latent representation is not easily interpreted by humans. In this paper, we propose training an auto-encoder that encodes input text into human-readable sentences. The auto-encoder is co...	rejected-papers	As expressed by most reviewers, the idea of the paper is interesting: using summarization as an intermediate representation for an auto encoder. In addition, a GAN is used on the generator output to encourage the output to look like summaries. They just need unpaired summaries. Even if the idea is interesting, from...	train	[ "B1JR9zaVz", "SyrgB9UEz", "HkSpi4cgz", "S1ms6cqxM", "B1_R9Digf", "Bkfuk3L7f", "H1HWq58Qz", "HyJUmo8XG" ]	[ "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "Thank you for reading the paper again and giving us comment. We will improve the writing of later sections. If we want to apply dual learning in this text summarization task, the training is not only on “source text -> summary -> source text”, but also on “summary -> source text -> summary”. In the “source text ->...	[ -1, -1, 5, 4, 6, -1, -1, -1 ]	[ -1, -1, 4, 4, 4, -1, -1, -1 ]	[ "SyrgB9UEz", "Bkfuk3L7f", "iclr_2018_r1kNDlbCb", "iclr_2018_r1kNDlbCb", "iclr_2018_r1kNDlbCb", "HkSpi4cgz", "B1_R9Digf", "S1ms6cqxM" ]
iclr_2018_Hy3MvSlRW	Adversarial reading networks for machine comprehension	Machine reading has recently shown remarkable progress thanks to differentiable reasoning models. In this context, End-to-End trainable Memory Networks (MemN2N) have demonstrated promising performance on simple natural language based reasoning tasks such as factual reasoning and basic deduction. Howev...	rejected-papers	The paper presents an adversarial learning framework for reading comprehension. Although the idea is interesting and presents an approach that ideally would make reading comprehension approaches more robust, the results are not substantially solid (see reviewer 3's comments) compared to other baselines to warrant acce...	train	[ "HynOT_5Jz", "BJggQbceG", "Sy0AiMnef" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "The paper aims to improve the accuracy of reading model on question answering dataset by playing against an adversarial agent (which is called narrator by the authors) that \"obfuscates\" the document, i.e. changing words in the document. The authors mention that word dropout can be considered as its special case ...	[ 4, 5, 5 ]	[ 5, 5, 4 ]	[ "iclr_2018_Hy3MvSlRW", "iclr_2018_Hy3MvSlRW", "iclr_2018_Hy3MvSlRW" ]
iclr_2018_r1QZ3zbAZ	Adversarial Examples for Natural Language Classification Problems	Modern machine learning algorithms are often susceptible to adversarial examples — maliciously crafted inputs that are undetectable by humans but that fool the algorithm into producing undesirable behavior. In this work, we show that adversarial examples exist in natural language classification: we formalize the notion...	rejected-papers	This paper presents a way to generate adversarial examples for text classification. The method is simple -- finding semantically similar words and replacing them in sentences with high language model score. The committee identifies weaknesses in this paper that resonate with the reviews below -- reviewer 1 suggests ...	train	[ "Byk2NS9xf", "HJKBdUKJf", "B1CfWm1WG", "Bk7QGoEQz", "SJx-zjVXz", "SkvobiEQz", "B1dv-jEmG", "SkuiQMmff", "BkMNGG7Gz", "BJNs1wMGG", "SJKx9Lzff", "B1BAtUMMG", "ByX3tUGGM", "S1E7t8fGz", "BJC9P7fMz", "SkkTnVJbz", "rJ7D9bpC-" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "public", "official_reviewer", "author", "author", "author", "author", "public", "public", "public" ]	[ "This paper proposes a method to generate adversarial examples for text classification problems. They do this by iteratively replacing words in a sentence with words that are close in its embedding space and which cause a change in the predicted class of the text. To preserve correct grammar, they only change words...	[ 4, 6, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 ]	[ 5, 3, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_r1QZ3zbAZ", "iclr_2018_r1QZ3zbAZ", "iclr_2018_r1QZ3zbAZ", "HJKBdUKJf", "Byk2NS9xf", "B1CfWm1WG", "BkMNGG7Gz", "BJNs1wMGG", "iclr_2018_r1QZ3zbAZ", "ByX3tUGGM", "rJ7D9bpC-", "HJKBdUKJf", "Byk2NS9xf", "B1CfWm1WG", "iclr_2018_r1QZ3zbAZ", "iclr_2018_r1QZ3zbAZ", "iclr_2018_r1QZ3...
iclr_2018_rybDdHe0Z	Sequence Transfer Learning for Neural Decoding	A fundamental challenge in designing brain-computer interfaces (BCIs) is decoding behavior from time-varying neural oscillations. In typical applications, decoders are constructed for individual subjects and with limited data leading to restrictions on the types of models that can be utilized. Currently, the best perfo...	rejected-papers	This paper tries to establish that LSTMs are suitable for modeling neural signals from the brain. However, the committee and most reviewers find that results are inconclusive. Results are mixed across subjects. We think it would have been far more interesting to compare other types of sequence models for this task o...	train	[ "HJ_bsmPxG", "HJmBCpKeG", "S1D3Hb9eM", "SyQDCnMNz", "H1S6vPofG", "HkJYOvsGG", "BkrakDsfz", "H1AvJwszG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "The paper describes an approach to use LSTM’s for finger classification based on ECOG. and a transfer learning extension of which two variations exists. From the presented results, the LSTM model is not an improvement over a basic linear model. The transfer learning models performs better than subject specific mod...	[ 4, 6, 3, -1, -1, -1, -1, -1 ]	[ 5, 5, 4, -1, -1, -1, -1, -1 ]	[ "iclr_2018_rybDdHe0Z", "iclr_2018_rybDdHe0Z", "iclr_2018_rybDdHe0Z", "H1S6vPofG", "HJ_bsmPxG", "HJ_bsmPxG", "HJmBCpKeG", "S1D3Hb9eM" ]
iclr_2018_HJ_X8GupW	Multi-label Learning for Large Text Corpora using Latent Variable Model with Provable Gurantees	Here we study the problem of learning labels for large text corpora where each document can be assigned a variable number of labels. The problem is trivial when the label dimensionality is small and can be easily solved by a series of one-vs-all classifiers. However, as the label dimensionality increases, the parameter...	rejected-papers	There is overall consensus about the paper's lack of novelty and clarity. Reviewer 1 has detailed comments that can be used to strengthen the paper. Reviewer 3 suggests that this paper is very close to Anandkumar et al 2012, and it is not clear where the novelty lies. Addressing these concerns of the reviewers will ...	train	[ "S1xUzwOgz", "B1ctU0uez", "B1ZszE9lG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "This paper studies the problem of multi-label learning for text copora. The paper proposed a latent variable model for the documents and their labels, and used spectral algorithms to provably learn the parameters.\n\nThe model is fairly simplistic: the topic can be one of k topics (pure topic model), based on the ...	[ 4, 3, 4 ]	[ 5, 4, 5 ]	[ "iclr_2018_HJ_X8GupW", "iclr_2018_HJ_X8GupW", "iclr_2018_HJ_X8GupW" ]
iclr_2018_r1AMITFaW	Dependent Bidirectional RNN with Extended-long Short-term Memory	In this work, we first conduct mathematical analysis on the memory, which is defined as a function that maps an element in a sequence to the current output, of three RNN cells; namely, the simple recurrent neural network (SRN), the long short-term memory (LSTM) and the gated recurrent unit (GRU). Base...	rejected-papers	The reviewers of the paper are not very enthusiastic of the new model proposed, nor are they very happy with the experiments presented. It is unclear from both the POS tagging and dependency parsing results where they stand with respect to state of the art methods that do not use RNNs. We understand that the idea is...	test	[ "SJ2iJmyeM", "ByNyuNYeM", "HyFOESYxM", "ryj3O097f", "SyWcVWC-M", "HyTiNZRZf", "HyI84ZCWG", "r1bUXZAWz", "rkM2fRtZf", "SkILbCF-z", "SJqHV0tZM", "HJ-W4RYZM", "S1fN-RtZz" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author" ]	[ "The paper proposes a new recurrent cell and a new way to make predictions for sequence tagging. It starts with a theoretical analysis of memory capabilities in different RNN cells and goes on with experiments on POS tagging and dependency parsing. There are serious presentation issues in the paper, which make it h...	[ 3, 4, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 ]	[ 4, 4, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_r1AMITFaW", "iclr_2018_r1AMITFaW", "iclr_2018_r1AMITFaW", "r1bUXZAWz", "ByNyuNYeM", "SJ2iJmyeM", "HyFOESYxM", "iclr_2018_r1AMITFaW", "ByNyuNYeM", "S1fN-RtZz", "HJ-W4RYZM", "SJ2iJmyeM", "HyFOESYxM" ]
iclr_2018_HJ39YKiTb	Associative Conversation Model: Generating Visual Information from Textual Information	In this paper, we propose the Associative Conversation Model that generates visual information from textual information and uses it for generating sentences in order to utilize visual information in a dialogue system without image input. In research on Neural Machine Translation, there are studies that generate transla...	rejected-papers	None of the reviewers are enthusiastic about the paper, primarily due to lack of proper evaluation. The response of the authors towards this criticism is also not sufficient. The final results are mixed which does not show very clearly that the presented associative model performs better than the sole seq2seq baselin...	val	[ "SySoIWLgf", "SJ4THI9gG", "BkC87_Cgz", "SkQSCdCmG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author" ]	[ "\n\nThe authors describe a method to be used in text dialogue systems. The contribution of the paper relies on the usage of visual information to enhance the performance of a dialogue system. An input phrase is expanded with visual information (visual context vectors), next visual and textual information is merged...	[ 4, 3, 3, -1 ]	[ 5, 4, 5, -1 ]	[ "iclr_2018_HJ39YKiTb", "iclr_2018_HJ39YKiTb", "iclr_2018_HJ39YKiTb", "iclr_2018_HJ39YKiTb" ]
iclr_2018_HypkN9yRW	DDRprog: A CLEVR Differentiable Dynamic Reasoning Programmer	We present a generic dynamic architecture that employs a problem specific differentiable forking mechanism to leverage discrete logical information about the problem data structure. We adapt and apply our model to CLEVR Visual Question Answering, giving rise to the DDRprog architecture; compared to previous approaches,...	rejected-papers	The reviewers generally agree that the DDRprog method is both novel and interesting, while also seeing merit in outperformance of related methods in the empirical results. However, There were a lot of complaints about the writing quality, the clarity of the exposition, and unclear motivation of some of the work. The r...	train	[ "BJZGbH9lz", "Sk3LFlJZf", "Byd74WfbM", "HkibWuTQM", "SJ7lW_pmM", "By8feuaXz", "rJQ-xu6XM", "HkQ3ydpXM", "SJqSJOamM" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author" ]	[ "\nSummary: This paper leverages an explicit program format and proposes a stack based RNN to solve question answering. The paper shows state-of-the art performance on the CLEVR dataset.\n\nClarity:\n- The description of the model is vague: I have to looking into appendix on what are the Cell and Controller functio...	[ 5, 5, 6, -1, -1, -1, -1, -1, -1 ]	[ 2, 2, 2, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_HypkN9yRW", "iclr_2018_HypkN9yRW", "iclr_2018_HypkN9yRW", "SJ7lW_pmM", "BJZGbH9lz", "rJQ-xu6XM", "Sk3LFlJZf", "Byd74WfbM", "iclr_2018_HypkN9yRW" ]
iclr_2018_r1TA9ZbA-	Learning to search with MCTSnets	Planning problems are among the most important and well-studied problems in artificial intelligence. They are most typically solved by tree search algorithms that simulate ahead into the future, evaluate future states, and back-up those evaluations to the root of a search tree. Among these algorithms, Monte-Carlo tree ...	rejected-papers	All reviewers agree that the contribution of this paper, a new way of training neural nets to execute Monte-Carlo Tree Search, is an appealing idea. For the most part, the reviewers found the exposition to be fairly clear, and the proposed architecture of good technical quality. Two of the reviewers point out flaws i...	val	[ "ByL3DP9gf", "HyC90Zoez", "HkTkZHjlM", "BySoOGDff", "ByptdGwfz", "r1bluMwMG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "The authors introduce an approach for adding learning to search capability to Monte Carlo tree search. The proposed method incorporates simulation-based search inside a neural network by expanding, evaluating and backing-up a vector-embedding. The key is to represent the internal state of the search by a memory ve...	[ 7, 4, 5, -1, -1, -1 ]	[ 3, 4, 4, -1, -1, -1 ]	[ "iclr_2018_r1TA9ZbA-", "iclr_2018_r1TA9ZbA-", "iclr_2018_r1TA9ZbA-", "ByL3DP9gf", "HyC90Zoez", "HkTkZHjlM" ]
iclr_2018_BkPrDFgR-	Piecewise Linear Neural Networks verification: A comparative study	The success of Deep Learning and its potential use in many important safety- critical applications has motivated research on formal verification of Neural Net- work (NN) models. Despite the reputation of learned NN models to behave as black boxes and theoretical hardness results of the problem of prov...	rejected-papers	All three reviewers are in agreement that this paper is not ready for ICLR in its current state. Given the pros/cons, the committee feels the paper is not ready for acceptance in its current form.	train	[ "ByZNy3ggM", "H1c3wqQef", "rkq9KFDlz", "SJFIDzpbG", "B1EHxS_bG", "ryngtRP-G", "Sk39OCPWf", "B1ZzuCwbM", "S122D0PZM", "SJGAoJ--f" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "public" ]	[ "The paper studies methods for verifying neural nets through their piecewise\nlinear structure. The authors survey different methods from the literature,\npropose a novel one, and evaluate them on a set of benchmarks.\n\nA major drawback of the evaluation of the different approaches is that\neverything was used wit...	[ 6, 5, 3, -1, -1, -1, -1, -1, -1, -1 ]	[ 3, 4, 5, -1, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_BkPrDFgR-", "iclr_2018_BkPrDFgR-", "iclr_2018_BkPrDFgR-", "B1EHxS_bG", "ryngtRP-G", "ByZNy3ggM", "H1c3wqQef", "rkq9KFDlz", "iclr_2018_BkPrDFgR-", "rkq9KFDlz" ]
iclr_2018_B1nxTzbRZ	Forward Modeling for Partial Observation Strategy Games - A StarCraft Defogger	This paper we present a defogger, a model that learns to predict future hidden information from partial observations. We formulate this model in the context of forward modeling and leverage spatial and sequential constraints and correlations via convolutional neural networks and long short-term memory networks, respect...	rejected-papers	The reviewer scores are fairly close, and the comments in their reviews are likewise similar. All reviewers indicate that they find this to be an interesting learning domain. However, they also agree in assessing the proposed method as having limited novelty and significance. They also critiqued the empirical evalua...	train	[ "SJ-MqkDVf", "HJr90mOlM", "BknmMUteM", "Sy46KdXfM", "rkoTsDaQz" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author" ]	[ "I appreciate the authors responses to my review, and their emphasis on task definition, but my other main concern about the work (poor evaluation --- no actual gameplay using defogger vs no defogger) remains. Also, the authors do not mention any added discussion about how to generalize their \"defogging\" task to...	[ -1, 5, 4, 5, -1 ]	[ -1, 4, 1, 3, -1 ]	[ "BknmMUteM", "iclr_2018_B1nxTzbRZ", "iclr_2018_B1nxTzbRZ", "iclr_2018_B1nxTzbRZ", "iclr_2018_B1nxTzbRZ" ]
iclr_2018_H1LAqMbRW	Latent forward model for Real-time Strategy game planning with incomplete information	Model-free deep reinforcement learning approaches have shown superhuman performance in simulated environments (e.g., Atari games, Go, etc). During training, these approaches often implicitly construct a latent space that contains key information for decision making. In this paper, we learn a forward model on this laten...	rejected-papers	There was certainly some interest in this paper which investigates learning latent models of the environment for model-based planning, particularly articulated by Reviewer3. However, the bulk of reviewer remarks focused on negatives, such as: --The model-based approach is disappointing compared to the model-free appr...	train	[ "BJ-32VOxf", "B1qenWKxM", "HJh2yfcgz", "rko8LBpXG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author" ]	[ "The paper proposes to use a pretrained model-free RL agent to extract the developed state representation and further re-use it for learning forward model of the environment and planning.\nThe idea of re-using a pretrained agent has both pros and cons. On one hand, it can be simpler than learning a model from scrat...	[ 5, 4, 4, -1 ]	[ 4, 5, 3, -1 ]	[ "iclr_2018_H1LAqMbRW", "iclr_2018_H1LAqMbRW", "iclr_2018_H1LAqMbRW", "iclr_2018_H1LAqMbRW" ]
iclr_2018_r15kjpHa-	Reward Design in Cooperative Multi-agent Reinforcement Learning for Packet Routing	In cooperative multi-agent reinforcement learning (MARL), how to design a suitable reward signal to accelerate learning and stabilize convergence is a critical problem. The global reward signal assigns the same global reward to all agents without distinguishing their contributions, while the local reward signal provide...	rejected-papers	All reviewers are unanimous that the paper is below threshold for acceptance. The authors have not provided rebuttals, but merely perfunctory generic responses. I think the most important criticism is that the approach is "very ad-hoc." I would encourage the authors to consider more principled ways of automatically ...	train	[ "r1OoL_Yxz", "rkY2B6KgM", "S1uz175xf", "HJ9oOJxZG", "r1JeKkgWM", "SkzCuyxZM" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "The authors suggest using a mixture of shared and individual rewards within a MARL environment to induce cooperation among independent agents. They show that on their specific application this can lead to a better overall global performance than purely sharing the global signal, or using just the independent rewar...	[ 5, 2, 5, -1, -1, -1 ]	[ 3, 4, 2, -1, -1, -1 ]	[ "iclr_2018_r15kjpHa-", "iclr_2018_r15kjpHa-", "iclr_2018_r15kjpHa-", "S1uz175xf", "r1OoL_Yxz", "rkY2B6KgM" ]
iclr_2018_SJvrXqvaZ	Adversary A3C for Robust Reinforcement Learning	Asynchronous Advantage Actor Critic (A3C) is an effective Reinforcement Learning (RL) algorithm for a wide range of tasks, such as Atari games and robot control. The agent learns policies and value function through trial-and-error interactions with the environment until converging to an optimal policy. Robustness and s...	rejected-papers	Reviewers are unanimous in scoring this paper below threshold for acceptance. The authors did not submit any rebuttals of the reviews. Pros: Paper is generally clear. Hardware results are valuable. Cons: Limited simulation results. Proposed method is not really novel. Insufficient empirical validation of the approac...	test	[ "S14kDbqlG", "r1tT8Ncez", "HJzp02rMM" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "Positive:\n- Interesting approach\n- Hardware validation (the RL field needs more of this!)\n\nNegative:\n- Figure 2: what is the reward here? The one from Section 5.1?\n- No comparisons to other methods: Single pendulum swing-up is a very easy task that has been solved with various methods (mostly in a cart-pole ...	[ 4, 4, 4 ]	[ 4, 4, 4 ]	[ "iclr_2018_SJvrXqvaZ", "iclr_2018_SJvrXqvaZ", "iclr_2018_SJvrXqvaZ" ]
iclr_2018_rJIN_4lA-	Maintaining cooperation in complex social dilemmas using deep reinforcement learning	Social dilemmas are situations where individuals face a temptation to increase their payoffs at a cost to total welfare. Building artificially intelligent agents that achieve good outcomes in these situations is important because many real world interactions include a tension between selfish interests and the welfare o...	rejected-papers	The reviewers found numerous issues in the paper, including unclear problem definitions, lack of motivation, no support for desiderata, clarity issues, points in discussion appearing to be technically incorrect, restrictive setting, sloppy definitions, and uninteresting experiments. Unfortunately, little note of posit...	train	[ "HkdM2LS4z", "Sya_dLrVz", "Sk2SPUSNz", "BkHI88rEM", "Skso_BrVz", "ryocOrBVf", "By8cjAVNM", "HJb7qCN4M", "H1CLw0V4G", "rkhkuoNgf", "B1_TQ-clG", "Bk_1Ws3xf", "SkKkV2qMM", "ByIQVhqGG", "By2P8nqGz", "ByKVU35fG", "rJDtLncGf", "rJg0Nh5zf" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "a...	[ "I feel like things are becoming more convoluted as we go along. Surely, agents \n\n\"remain on the equilibrium path because of what they anticipate would happen if\nthey were to deviate\" -- Binmore (1992)\n\nBut this is a statement that holds for general games, I don't see how this helps define a \"social dilemma...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 3, -1, -1, -1, -1, -1, -1 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 5, -1, -1, -1, -1, -1, -1 ]	[ "ryocOrBVf", "Skso_BrVz", "Skso_BrVz", "Skso_BrVz", "ryocOrBVf", "By8cjAVNM", "rJDtLncGf", "By2P8nqGz", "ByKVU35fG", "iclr_2018_rJIN_4lA-", "iclr_2018_rJIN_4lA-", "iclr_2018_rJIN_4lA-", "Bk_1Ws3xf", "SkKkV2qMM", "ByKVU35fG", "rkhkuoNgf", "By2P8nqGz", "B1_TQ-clG" ]
iclr_2018_B1EGg7ZCb	Autonomous Vehicle Fleet Coordination With Deep Reinforcement Learning	Autonomous vehicles are becoming more common in city transportation. Companies will begin to find a need to teach these vehicles smart city fleet coordination. Currently, simulation based modeling along with hand coded rules dictate the decision making of these autonomous vehicles. We believe that complex intelligent...	rejected-papers	The reviewers agree that the manuscript is below the acceptance threshold at ICLR. Many points of criticism were evident in the reviewer comments, including small artificial test domain, no new methods introduced, poor writing in some places, and dubious need for DeepRL in this domain. The reviews mentioned a number ...	train	[ "Hy73csVeG", "HyqzL3Ogz", "rJJxcdqeM" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "\n\nThis paper proposes to use deep reinforcement learning to solve a multiagent coordination task. In particular, the paper introduces a benchmark domain to model fleet coordination problems as might be encountered in taxi companies. \n\nThe paper does not really introduce new methods, and as such, this paper sho...	[ 3, 3, 4 ]	[ 5, 3, 4 ]	[ "iclr_2018_B1EGg7ZCb", "iclr_2018_B1EGg7ZCb", "iclr_2018_B1EGg7ZCb" ]
iclr_2018_rye7IMbAZ	Explicit Induction Bias for Transfer Learning with Convolutional Networks	In inductive transfer learning, fine-tuning pre-trained convolutional networks substantially outperforms training from scratch. When using fine-tuning, the underlying assumption is that the pre-trained model extracts generic features, which are at least partially relevant for solving the target task, but would be...	rejected-papers	This paper addresses the question of how to regularize when starting from a pre-trained convolutional network in the context of transfer learning. The authors propose to regularize toward the parameters of the pre-trained model and study multiple regularizers of this type. The experiments are thorough and convincing ...	train	[ "ryD53e9xG", "Hku7RS6lf", "BJQD_I_eM", "S1A91_pmM", "BkoNYvaXf", "SylgFP6Xz", "BkbKdDT7G" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "This work addresses the scenario of fine-tuning a pre-trained network for new data/tasks and empirically studies various regularization techniques. Overall, the evaluation concludes with recommending that all layers of a network whose weights are directly transferred during fine-tuning should be regularized agains...	[ 6, 7, 6, -1, -1, -1, -1 ]	[ 5, 4, 4, -1, -1, -1, -1 ]	[ "iclr_2018_rye7IMbAZ", "iclr_2018_rye7IMbAZ", "iclr_2018_rye7IMbAZ", "iclr_2018_rye7IMbAZ", "ryD53e9xG", "BJQD_I_eM", "Hku7RS6lf" ]
iclr_2018_rkZzY-lCb	Feat2Vec: Dense Vector Representation for Data with Arbitrary Features	Methods that calculate dense vector representations for features in unstructured data—such as words in a document—have proven to be very successful for knowledge representation. We study how to estimate dense representations when multiple feature types exist within a dataset for supervised learning where explicit label...	rejected-papers	The paper presents an approach for learning continuous-valued vector representations combining multiple input feature sets of different types, in both unsupervised and supervised settings. The revised paper is a merger of the original submission and another ICLR submission. This meta-review takes into account all of ...	train	[ "HJoZquUSM", "rJygCYHHM", "r1_2VGLlz", "HJfRKPFeM", "ByQ1mb0xM", "H1cuqDpXf", "SJSx5wTmz", "Bk_CuPamf", "rkNuOP6XG" ]	[ "author", "public", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "Thank you for your insightful comments.\n\nI. NOVELTY\nAfter reviewing your two references, we believe that our novelty claims still stand:\n\n1) Regarding the \"exponential family embeddings,\" our claim refers to general-purpose embeddings, which we define as “embeddings of an unsupervised method that can be use...	[ -1, -1, 7, 2, 7, -1, -1, -1, -1 ]	[ -1, -1, 3, 2, 5, -1, -1, -1, -1 ]	[ "rJygCYHHM", "iclr_2018_rkZzY-lCb", "iclr_2018_rkZzY-lCb", "iclr_2018_rkZzY-lCb", "iclr_2018_rkZzY-lCb", "iclr_2018_rkZzY-lCb", "HJfRKPFeM", "r1_2VGLlz", "ByQ1mb0xM" ]
iclr_2018_H18uzzWAZ	Correcting Nuisance Variation using Wasserstein Distance	Profiling cellular phenotypes from microscopic imaging can provide meaningful biological information resulting from various factors affecting the cells. One motivating application is drug development: morphological cell features can be captured from images, from which similarities between different drugs applied at dif...	rejected-papers	This is a nice but very narrow study of domain invariance in a microscopic imaging application. Since the problem is very general, the paper should include much more substantial context, e.g. discussion of various alternative methods (e.g. the ones cited in Sun et al. 2017). In order to contribute to the broader ICLR...	val	[ "Hkyq_kqgz", "HJk2HZqxM", "SkvdG35xz", "ByRaH8pXM", "BJoM5IpXG", "Bk5rFIamG", "rkIzDL67M", "HyAuXL6Qf", "S1HeGU6Xf" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author" ]	[ "The paper discusses a method for adjusting image embeddings in order tease apart technical variation from biological signal. A loss function based on the Wasserstein distance is used. \nThe paper is interesting but could certainly do with more explanations. \n\nComments:\n1. It is difficult for the reader to under...	[ 5, 4, 7, -1, -1, -1, -1, -1, -1 ]	[ 3, 5, 3, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_H18uzzWAZ", "iclr_2018_H18uzzWAZ", "iclr_2018_H18uzzWAZ", "HJk2HZqxM", "Hkyq_kqgz", "HJk2HZqxM", "HJk2HZqxM", "SkvdG35xz", "iclr_2018_H18uzzWAZ" ]
iclr_2018_BJvVbCJCb	Neural Clustering By Predicting And Copying Noise	We propose a neural clustering model that jointly learns both latent features and how they cluster. Unlike similar methods our model does not require a predefined number of clusters. Using a supervised approach, we agglomerate latent features towards randomly sampled targets within the same space whilst progressively r...	rejected-papers	The paper proposes an approach to jointly learning a data clustering and latent representation. The main selling point is that the number of clusters need not be pre-specified. However, there are other hyperparameters and it is not clear why trading # clusters for other hyperparameters is a win. The empirical result...	train	[ "ryMv4SZ7M", "rkX7hRmeM", "Hk2HKdrlz", "H1flxytxf", "SyR-e8uWG", "rJmxgLuZG", "r1l0JIdWz", "SyUwqSoJf", "HJyr5Hokf", "SkrcjjVJM" ]	[ "author", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "public" ]	[ "We have made some changes and additions to the paper during this rebuttal/discussion period. Our main changes are to add further experiments to demonstrate the robustness of the NATAC training method, and to add more baselines to our text-based experiments. In full, we have:\n\n* Added other clustering methods int...	[ -1, 5, 5, 5, -1, -1, -1, -1, -1, -1 ]	[ -1, 4, 3, 4, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_BJvVbCJCb", "iclr_2018_BJvVbCJCb", "iclr_2018_BJvVbCJCb", "iclr_2018_BJvVbCJCb", "rkX7hRmeM", "Hk2HKdrlz", "H1flxytxf", "SkrcjjVJM", "iclr_2018_BJvVbCJCb", "iclr_2018_BJvVbCJCb" ]
iclr_2018_S191YzbRZ	Prototype Matching Networks for Large-Scale Multi-label Genomic Sequence Classification	One of the fundamental tasks in understanding genomics is the problem of predicting Transcription Factor Binding Sites (TFBSs). With more than hundreds of Transcription Factors (TFs) as labels, genomic-sequence based TFBS prediction is a challenging multi-label classification task. There are two major biological mechan...	rejected-papers	This paper proposes an approach for predicting transcription factor (TF) binding sites and TF-TF interaction. The approach is interesting and may ultimately be valuable for the intended application. But in its current state, the paper has insufficient technical novelty (e.g. relative to matching networks of Vinyals ...	val	[ "ryoWUP5lz", "HkM_FfLxM", "H1yqn7qlM", "ByJ37P67M", "rJn6VDaQf", "HJa3NwT7z", "r1Tj4DTQG", "By6F4v6Qz", "ryJY4Dp7f", "ByMwEP67z", "rk-UVPTmM", "Hk2EVPTQG", "H11bNPamG", "SJjyVwpXz", "SJJsmwp7z", "SkGY7vTXz", "HkmwQwpXf", "rJZSXvpXf" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author" ]	[ "This work proposes an approach for transcription factor binding site prediction using a multi-label classification formulation. It is a very interesting problem and application and the approach is interesting. \n\nNovelty:\nThe method is quite similar to matching networks (Vinyals, 2016) with a few changes in the ...	[ 5, 5, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 ]	[ 4, 5, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_S191YzbRZ", "iclr_2018_S191YzbRZ", "iclr_2018_S191YzbRZ", "ryoWUP5lz", "HkM_FfLxM", "HkM_FfLxM", "HkM_FfLxM", "HkM_FfLxM", "HkM_FfLxM", "H1yqn7qlM", "H1yqn7qlM", "H1yqn7qlM", "H1yqn7qlM", "H1yqn7qlM", "ryoWUP5lz", "ryoWUP5lz", "ryoWUP5lz", "ryoWUP5lz" ]
iclr_2018_SJzmJEq6W	Learning non-linear transform with discriminative and minimum information loss priors	This paper proposes a novel approach for learning discriminative and sparse representations. It consists of utilizing two different models. A predefined number of non-linear transform models are used in the learning stage, and one sparsifying transform model is used at test time. The non-linear transform models have di...	rejected-papers	This paper proposes an approach for learning a sparsifying transform via a set of nonlinear transforms at learning time. The presentation needs a lot of work. The original paper was 17 pages long and very difficult to understand. The revised paper is 12 pages long, which is still too long for the content. The paper...	train	[ "BkTGJ-9EM", "rJiAXzOVM", "Sy8Kdltgz", "HykAaKDgf", "BJy3xb9xM", "Hy5qs4_ZM", "ry7q9yQZf", "r1kudkmbz", "H1mVDJ7Wf" ]	[ "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "To all reviewers, we would like to extend the appreciation for taking the necessary time, involvement and effort in reading our initial and rebutted paper version, express our gratitude for all the taken considerations, raised comments and concerns about all aspects of this paper, contributing towards increasing t...	[ -1, -1, 5, 4, 5, -1, -1, -1, -1 ]	[ -1, -1, 2, 2, 1, -1, -1, -1, -1 ]	[ "iclr_2018_SJzmJEq6W", "Sy8Kdltgz", "iclr_2018_SJzmJEq6W", "iclr_2018_SJzmJEq6W", "iclr_2018_SJzmJEq6W", "iclr_2018_SJzmJEq6W", "HykAaKDgf", "Sy8Kdltgz", "BJy3xb9xM" ]
iclr_2018_r1tJKuyRZ	The Set Autoencoder: Unsupervised Representation Learning for Sets	We propose the set autoencoder, a model for unsupervised representation learning for sets of elements. It is closely related to sequence-to-sequence models, which learn fixed-sized latent representations for sequences, and have been applied to a number of challenging supervised sequence tasks such as machine translatio...	rejected-papers	The paper proposes an autoencoder for sets, an interesting and timely problem. The encoder here is based on prior related work (Vinyals et al. 2016) while the decoder uses a loss based on finding a matching between the input and output set elements. Experiments on multiple data sets are given, but none are realistic....	train	[ "rk7TfpBlG", "B1EnXjFxG", "Hk-Qowclf", "rkyAcO7NM", "r1WktiLGG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author" ]	[ "This paper mostly extends Vinyals et al, 2015 paper (\"Order Matters\") on how to represent sets as input and/or output of a deep architecture.\n\nAs far as I understood, the set encoder is the same as the one in \"Order Matters\". If not, it would be useful to underline the differences.\n\nThe decoder, on the oth...	[ 4, 5, 5, -1, -1 ]	[ 5, 4, 4, -1, -1 ]	[ "iclr_2018_r1tJKuyRZ", "iclr_2018_r1tJKuyRZ", "iclr_2018_r1tJKuyRZ", "rk7TfpBlG", "iclr_2018_r1tJKuyRZ" ]
iclr_2018_B1EVwkqTW	Make SVM great again with Siamese kernel for few-shot learning	While deep neural networks have shown outstanding results in a wide range of applications, learning from a very limited number of examples is still a challenging task. Despite the difficulties of the few-shot learning, metric-learning techniques showed the potential of the neural networks for this tas...	rejected-papers	This paper proposes to pre-train a feature embedding, using Siamese networks, for use with few-shot learning for SVMs. The idea is not very novel since there is a fairly large body of work in the general setting of pre-trained features + simple predictor. In addition, the experimental results could be stronger -- the...	train	[ "B1jQdMSeG", "BkatreVxM", "SybmxPplz", "r1a99OpWz", "B1VE6DTZG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author" ]	[ "After reading the rebuttal:\n\nThis paper does have encouraging results. But as mentioned earlier, it still lacks systematic comparisons with existing (and strongest) baselines, and perhaps a better understanding the differences between approaches and the pros and cons. The writing also needs to be improved. So I ...	[ 5, 3, 4, -1, -1 ]	[ 4, 4, 5, -1, -1 ]	[ "iclr_2018_B1EVwkqTW", "iclr_2018_B1EVwkqTW", "iclr_2018_B1EVwkqTW", "B1jQdMSeG", "SybmxPplz" ]
iclr_2018_BkVf1AeAZ	Label Embedding Network: Learning Label Representation for Soft Training of Deep Networks	We propose a method, called Label Embedding Network, which can learn label representation (label embedding) during the training process of deep networks. With the proposed method, the label embedding is adaptively and automatically learned through back propagation. The original one-hot represented loss function is conv...	rejected-papers	This paper proposes an approach for jointly learning a label embedding and prediction network, as a way of taking advantage of relationships between labels. This general idea is well-motivated, but the specifics of the proposed approach are not motivated or described well. More discussion of relationship with prior w...	train	[ "Hk7pW6HlM", "SyZf4f5gM", "r1zEZ9ief", "By15nh6eG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "public" ]	[ "The paper proposes to add an embedding layer for labels that constrains normal classifiers in order to find label representations that are semantically consistent. The approach is then experimented on various image and text tasks.\n\nThe description of the model is laborious and hard to follow. Figure 1 helps but ...	[ 4, 4, 3, -1 ]	[ 5, 3, 4, -1 ]	[ "iclr_2018_BkVf1AeAZ", "iclr_2018_BkVf1AeAZ", "iclr_2018_BkVf1AeAZ", "iclr_2018_BkVf1AeAZ" ]
iclr_2018_HJsk5-Z0W	Structured Deep Factorization Machine: Towards General-Purpose Architectures	In spite of their great success, traditional factorization algorithms typically do not support features (e.g., Matrix Factorization), or their complexity scales quadratically with the number of features (e.g, Factorization Machine). On the other hand, neural methods allow large feature sets, but are often designed for ...	rejected-papers	This paper has been withdrawn by the authors.	train	[ "rkSyVFDeG", "Bk0lEg6eG", "Sk6iGkvbG", "SJrX6Hpmz" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author" ]	[ "This paper proposes to improve time complexity of factorization machine. Unfortunately, the paper's claim that FM's time complexity is quadratic to feature size is wrong. Specifically, the dot product can be computed as (which is linear to feature size)\n\n(\\sum x_i \\beta_i)^T (\\sum x_i \\beta_i) - \\sum_i x_i^...	[ 3, 4, 4, -1 ]	[ 5, 5, 3, -1 ]	[ "iclr_2018_HJsk5-Z0W", "iclr_2018_HJsk5-Z0W", "iclr_2018_HJsk5-Z0W", "iclr_2018_HJsk5-Z0W" ]
iclr_2018_SyGT_6yCZ	Simple Fast Convolutional Feature Learning	The quality of the features used in visual recognition is of fundamental importance for the overall system. For a long time, low-level hand-designed feature algorithms as SIFT and HOG have obtained the best results on image recognition. Visual features have recently been extracted from trained convolutional neural netw...	rejected-papers	The paper addresses the training time of CNNs, in the common setting where a CNN is trained on one domain and then used to extract features for another domain. The paper proposes to speed up the CNN training step via a particular proposed training schedule with a reduced number of epochs. Training time of the pre-tra...	val	[ "SyWq1JvlM", "rk0P3FdeM", "rJUMQfpeM", "rJXa_V5Zz", "r1L6779WM", "ByZqDFKWG", "HkTny32gM", "Bkou3Wjez" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "public", "author", "public" ]	[ "This paper deals with early stopping but the contributions are limited. This work would fit better a workshop as a preliminary result, furthermore it is too short. Following a short review section per section.\n\nIntro: The name SFC is misleading as the method consists in stopping early the training with an optimi...	[ 3, 3, 2, -1, -1, -1, -1, -1 ]	[ 4, 4, 4, -1, -1, -1, -1, -1 ]	[ "iclr_2018_SyGT_6yCZ", "iclr_2018_SyGT_6yCZ", "iclr_2018_SyGT_6yCZ", "rJUMQfpeM", "ByZqDFKWG", "iclr_2018_SyGT_6yCZ", "Bkou3Wjez", "iclr_2018_SyGT_6yCZ" ]
iclr_2018_r1cLblgCZ	Recurrent Auto-Encoder Model for Multidimensional Time Series Representation	Recurrent auto-encoder model can summarise sequential data through an encoder structure into a fixed-length vector and then reconstruct into its original sequential form through the decoder structure. The summarised information can be used to represent time series features. In this paper, we propose relaxing the dimens...	rejected-papers	This paper applies a form of recurrent autoencoder for a specific type of industrial sensor signal analysis. The application is very narrow and the data set is proprietary. The approach is not clearly described, but seems very straightforward and is not placed in context of prior work. It is therefore not clear how ...	train	[ "HJI6Rf1eG", "r1CkPdteG", "BkPl4O9xM", "S1XLye3QG", "SkLr9127f", "HkHE9y27G", "B1oGcJ27M" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "This writeup describes an application of recurrent autoencoder to analysis of multidimensional time series. The quality of writing, experimentation and scholarship is clearly below than what is expected from a scientific article. The method is explained in a very unclear way, there is no mention of any related wor...	[ 2, 2, 4, -1, -1, -1, -1 ]	[ 4, 5, 4, -1, -1, -1, -1 ]	[ "iclr_2018_r1cLblgCZ", "iclr_2018_r1cLblgCZ", "iclr_2018_r1cLblgCZ", "iclr_2018_r1cLblgCZ", "HJI6Rf1eG", "r1CkPdteG", "BkPl4O9xM" ]
iclr_2018_H1uP7ebAW	Learning to diagnose from scratch by exploiting dependencies among labels	The field of medical diagnostics contains a wealth of challenges which closely resemble classical machine learning problems; practical constraints, however, complicate the translation of these endpoints naively into classical architectures. Many tasks in radiology, for example, are largely problems of multi-label class...	rejected-papers	Authors apply dense nets and LSTM to model dependencies among labels and demonstrate new state-of-art performance on an X-Ray dataset. Pros: - Well written. - New improvement to state-of-art Cons: - Novelties are not strong. One combination of existing approaches are used to achieve state-of-art on what is still a re...	train	[ "HJZ2MKRbM", "S1KuIB5gz", "BkE5LPlZG", "SyAfEqafG", "BJoLLcTMM", "BkpwSqpMG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "public", "public", "public" ]	[ "The paper proposes to combine the recently proposed DenseNet architecture with LSTMs to tackle the problem of predicting different pathologic patterns from chest x-rays. In particular, the use of LSTMs helps take into account interdependencies between pattern labels. \n\nStrengths:\n- The paper is very well writte...	[ 6, 6, 6, -1, -1, -1 ]	[ 3, 4, 3, -1, -1, -1 ]	[ "iclr_2018_H1uP7ebAW", "iclr_2018_H1uP7ebAW", "iclr_2018_H1uP7ebAW", "HJZ2MKRbM", "S1KuIB5gz", "BkE5LPlZG" ]
iclr_2018_ryserbZR-	Classification and Disease Localization in Histopathology Using Only Global Labels: A Weakly-Supervised Approach	Analysis of histopathology slides is a critical step for many diagnoses, and in particular in oncology where it defines the gold standard. In the case of digital histopathological analysis, highly trained pathologists must review vast whole-slide-images of extreme digital resolution (100,000^2 pixels) across multiple z...	rejected-papers	Authors present a method for disease classification and localization in histopathology images. Standard image processing techniques are used to extract and normalize tiles of tissue, after which features are extracted from pertained networks. A 1-D convolutional filter is applied to the bag of features from the tiles (...	test	[ "S1O8uhkxf", "SkWQLvebf", "Bk72o4NWM", "BkH_ar6XM", "Byy2THTQG", "BJDr6HaXM", "BJ8riS6Qf", "Hy1koS67M", "rkmE5raXf", "r1WptBaXz", "rkjIwbqxM" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "public" ]	[ "This paper describes a semi-supervised method to classify and segment WSI histological images that are only labeled at the whole image level. Images are tiled and tiles are sampled and encoded into a feature vector via a ResNET-50 pretrained on ImageNET. A 1D convolutional layer followed by a min-max layer and 2 f...	[ 5, 6, 5, -1, -1, -1, -1, -1, -1, -1, -1 ]	[ 4, 3, 3, -1, -1, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_ryserbZR-", "iclr_2018_ryserbZR-", "iclr_2018_ryserbZR-", "Bk72o4NWM", "Bk72o4NWM", "Bk72o4NWM", "S1O8uhkxf", "SkWQLvebf", "iclr_2018_ryserbZR-", "iclr_2018_ryserbZR-", "iclr_2018_ryserbZR-" ]
iclr_2018_rk1FQA0pW	End-to-End Abnormality Detection in Medical Imaging	Deep neural networks (DNN) have shown promising performance in computer vision. In medical imaging, encouraging results have been achieved with deep learning for applications such as segmentation, lesion detection and classification. Nearly all of the deep learning based image analysis methods work on reconstructed ima...	rejected-papers	Authors present an evaluation of end-to-end training connecting reconstruction network with detection network for lung nodules. Pros: - Optimizing a mapping jointly with the task may preserve more information that is relevant to the task. Cons: - Reconstruction network is not "needed" to generate an image -- other al...	train	[ "SkoQMHqlG", "S1gaKDqlM", "Byyu-H4-f" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "The paper proposes a DNN for patch-based lung nodule detection, directly from the CT projection data. The two-component network, comprising of the reconstruction network and the nodule detection network, is trained end-to-end. The trained network was validated on a simulated dataset of 1018\tlow-dose chest CT imag...	[ 4, 5, 6 ]	[ 4, 4, 3 ]	[ "iclr_2018_rk1FQA0pW", "iclr_2018_rk1FQA0pW", "iclr_2018_rk1FQA0pW" ]
iclr_2018_HkJ1rgbCb	Using Deep Reinforcement Learning to Generate Rationales for Molecules	Deep learning algorithms are increasingly used in modeling chemical processes. However, black box predictions without rationales have limited used in practical applications, such as drug design. To this end, we learn to identify molecular substructures -- rationales -- that are associated with the target chemical prope...	rejected-papers	Pro: - Interesting approach to tie together reinforcement Q-learning with CNN for prediction and reward function learning in predicting downstream effects of chemical structures, while providing relevant areas for decision-making. Con: - Datasets are small, generalizability not clear. - Performance is not high (alth...	train	[ "r11LXabJz", "S1wvy15xz", "SyI8c-T-f", "ByLbXBdzM", "ByqZ04_GG", "H1iOTE_fz" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "\nThe paper proposes a feature learning technique for molecular prediction using reinforcement learning. The predictive model is an interesting two-step approach where important atoms of the molecule are added one-by-one with a reward given by a second Q-network that learns how well we can solve the prediction pro...	[ 5, 5, 5, -1, -1, -1 ]	[ 4, 4, 4, -1, -1, -1 ]	[ "iclr_2018_HkJ1rgbCb", "iclr_2018_HkJ1rgbCb", "iclr_2018_HkJ1rgbCb", "S1wvy15xz", "r11LXabJz", "SyI8c-T-f" ]
iclr_2018_HytSvlWRZ	Subspace Network: Deep Multi-Task Censored Regression for Modeling Neurodegenerative Diseases	Over the past decade a wide spectrum of machine learning models have been developed to model the neurodegenerative diseases, associating biomarkers, especially non-intrusive neuroimaging markers, with key clinical scores measuring the cognitive status of patients. Multi-task learning (MTL) has been extensively explored...	rejected-papers	Authors present a method for modeling neurodegenerative diseases using a multitask learning framework that considers "censored regression" problems (to model where the outputs have discrete values and ranges). Given the pros/cons, the committee feels this paper is not ready for acceptance in its current state. Pro: -...	train	[ "SkwZAL4ef", "r1z2QSOlz", "B1r0SU9gz", "Skzmnk2mf", "SyFl9LxQf", "H189gvyQM", "ByQ7kvkmf", "BJl30LJ7G", "BkE02U1Xf", "rJ2_MDJXf" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author" ]	[ "This work proposes a multi task learning framework for the modeling of clinical data in neurodegenerative diseases. \nDifferently from previous applications of machine learning in neurodegeneration modeling, the proposed approach models the clinical data accounting for the bounded nature of cognitive tests scores....	[ 4, 5, 5, -1, -1, -1, -1, -1, -1, -1 ]	[ 5, 3, 4, -1, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_HytSvlWRZ", "iclr_2018_HytSvlWRZ", "iclr_2018_HytSvlWRZ", "iclr_2018_HytSvlWRZ", "iclr_2018_HytSvlWRZ", "SkwZAL4ef", "BJl30LJ7G", "B1r0SU9gz", "r1z2QSOlz", "H189gvyQM" ]
iclr_2018_HkanP0lRW	Data-driven Feature Sampling for Deep Hyperspectral Classification and Segmentation	The high dimensionality of hyperspectral imaging forces unique challenges in scope, size and processing requirements. Motivated by the potential for an in-the-field cell sorting detector, we examine a Synechocystis sp. PCC 6803 dataset wherein cells are grown alternatively in nitrogen rich or deplete cultures. We use...	rejected-papers	Area chair is in agreement with reviewers: this is a good experiment that successfully applies specific machine learning techniques to the particular task. However, the authors have not discussed or studied the breadth of other possible methods that could also solve the given task ... besides those mentioned by the rev...	train	[ "HyrFUnNgf", "rkEn8swgG", "S12q91ZZM" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "Authors propose a greedy scheme to select a subset of (highly correlated) spectral features in a classification task. The selection criterion used is the average magnitude with which this feature contributes to the activation of a next-layer perceptron. Once validation accuracy drops too much, the pruned network i...	[ 3, 6, 4 ]	[ 5, 5, 5 ]	[ "iclr_2018_HkanP0lRW", "iclr_2018_HkanP0lRW", "iclr_2018_HkanP0lRW" ]
iclr_2018_H1K6Tb-AZ	TESLA: Task-wise Early Stopping and Loss Aggregation for Dynamic Neural Network Inference	For inference operations in deep neural networks on end devices, it is desirable to deploy a single pre-trained neural network model, which can dynamically scale across a computation range without comprising accuracy. To achieve this goal, Incomplete Dot Product (IDP) has been proposed to use only a subset of terms in ...	rejected-papers	General consensus among reviewers that paper does not meet criteria for publication. Pro: - Improvement over the original IDP proposal. - Some promising preliminary results. Con: - Insufficient comparison to other methods of network compression, - Insufficient comparison to other datasets (such as ImageNet) - Insuffi...	train	[ "SJF0AbKgG", "rJyYwFhlz", "r1VT-4J-z", "SykDmN6Xz", "ryaL9Qp7G", "S11DgXamf" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "An approach to adjust inference speed, power consumption or latency by using incomplete dot products McDanel et al. (2017) is investigated.\n\nThe approach is based on `profile coefficients’ which are learned for every channel in a convolution layer, or for every column in the fully connected layer. Based on the m...	[ 4, 5, 4, -1, -1, -1 ]	[ 4, 2, 2, -1, -1, -1 ]	[ "iclr_2018_H1K6Tb-AZ", "iclr_2018_H1K6Tb-AZ", "iclr_2018_H1K6Tb-AZ", "SJF0AbKgG", "rJyYwFhlz", "r1VT-4J-z" ]
iclr_2018_HkjL6MiTb	Siamese Survival Analysis with Competing Risks	Survival Analysis (time-to-event analysis) in the presence of multiple possible adverse events, i.e., competing risks, is a challenging, yet very important problem in medicine, finance, manufacturing, etc. Extending classical survival analysis to competing risks is not trivial since only one event (e.g. one cause of de...	rejected-papers	Reviewers unanimous in assessment that manuscript has merits, but does not satisfy criteria for publication. Pros: - Potentially novel application of neural networks to survival analysis with competing risks, where only one terminal event from one risk category may be observed. Cons: - Incomplete coverage of other li...	train	[ "SyJXpk5lG", "SkpfobogG", "rkOt8g2ef", "H106JBomz", "SyZNJHimz", "SksVpEimG", "ByYiANimf", "HkcPpViXf" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author" ]	[ "This paper introduces siamese neural networks to the competing risks framework of Fine and Gray. The authors optimize for the c-index by minimizing a loss function driven by the cumulative risk of competing risk m and correct ordering of comparable pairs. While the idea of optimizing directly for the c-index direc...	[ 4, 4, 4, -1, -1, -1, -1, -1 ]	[ 4, 4, 5, -1, -1, -1, -1, -1 ]	[ "iclr_2018_HkjL6MiTb", "iclr_2018_HkjL6MiTb", "iclr_2018_HkjL6MiTb", "SyJXpk5lG", "ByYiANimf", "rkOt8g2ef", "SkpfobogG", "SksVpEimG" ]
iclr_2018_ByJbJwxCW	Relational Multi-Instance Learning for Concept Annotation from Medical Time Series	Recent advances in computing technology and sensor design have made it easier to collect longitudinal or time series data from patients, resulting in a gigantic amount of available medical data. Most of the medical time series lack annotations or even when the annotations are available they could be subjective and pron...	rejected-papers	This paper presents a MIL method for medical time series data. General consensus among reviewers that work does not meet criteria for being accepted. Specifically: Pros: - A variety of meta-learning parameters are evaluated for the task at hand. - Minor novelty of the proposed method Cons: - Minor novelty of the pro...	train	[ "Hk2mNy-gG", "rkcWXX9gf", "Hyu6DTogG", "Skeyh697G", "r1ozjTcQM", "SyYWc6qQG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "The paper addresses the classification of medical time-series data by formulating the problem as a multi-instance learning (MIL) task, where there is an instance for each timestep of each time series, labels are observed at the time-series level (i.e. for each bag), and the goal is to perform instance-level and se...	[ 6, 3, 3, -1, -1, -1 ]	[ 4, 3, 5, -1, -1, -1 ]	[ "iclr_2018_ByJbJwxCW", "iclr_2018_ByJbJwxCW", "iclr_2018_ByJbJwxCW", "Hk2mNy-gG", "rkcWXX9gf", "Hyu6DTogG" ]
iclr_2018_SJFM0ZWCb	Deep Temporal Clustering: Fully unsupervised learning of time-domain features	Unsupervised learning of timeseries data is a challenging problem in machine learning. Here, we propose a novel algorithm, Deep Temporal Clustering (DTC), a fully unsupervised method, to naturally integrate dimensionality reduction and temporal clustering into a single end to end learning framework. The algorith...	rejected-papers	Joint optimization of dimensionality reduction and temporal clusters. Results suggest performance improvement in a variety of scenarios versus a baseline of a recent state-of-art clustering method. Pro: - Joint optimization may be new and results suggest performance improvement when done on NASA Magnetospheric Multisc...	train	[ "ryMizdDef", "rkq18W9eG", "HyWGBr5lf" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "The authors proposed an algorithm named Deep Temporal Clustering (DTC) that integrates autoencoder with time-series data clustering. Compared to existing methods, DTC used a network structure (CNN + BiLSTM) that suits time-series data. In addition, a new clustering loss with different similarity measures are adopt...	[ 3, 5, 4 ]	[ 5, 4, 4 ]	[ "iclr_2018_SJFM0ZWCb", "iclr_2018_SJFM0ZWCb", "iclr_2018_SJFM0ZWCb" ]
iclr_2018_rJr4kfWCb	Lung Tumor Location and Identification with AlexNet and a Custom CNN	Lung cancer is the leading cause of cancer deaths in the world and early detection is a crucial part of increasing patient survival. Deep learning techniques provide us with a method of automated analysis of patient scans. In this work, we compare AlexNet, a multi-layered and highly ﬂexible architecture, with a custom ...	rejected-papers	Pros: - Addresses an important medical imaging application - Uses an open dataset Con: - Authors do not cite original article describing challenge from which they use their data: https://arxiv.org/pdf/1612.08012.pdf , or the website for the corresponding challenge: https://luna16.grand-challenge.org/results/ - Authors...	train	[ "HkQQ3IQxf", "B1dApr_lf", "SkOp9W5gf", "rk24sxMzf", "Hk36mQzfz", "rkWJCpgGM", "SkbN34JWz" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "public", "public", "public", "public" ]	[ "This paper compares 2 CNN architectures (Alexnet and a VGG variant) for the task of classifying images of lung cancer from CT scans. The comparison is trivial and does not go in depth to explain why one architecture works better than the other. Also, no effort is made to explain the data beyond some superficial de...	[ 2, 3, 3, -1, -1, -1, -1 ]	[ 5, 4, 4, -1, -1, -1, -1 ]	[ "iclr_2018_rJr4kfWCb", "iclr_2018_rJr4kfWCb", "iclr_2018_rJr4kfWCb", "iclr_2018_rJr4kfWCb", "iclr_2018_rJr4kfWCb", "iclr_2018_rJr4kfWCb", "iclr_2018_rJr4kfWCb" ]
iclr_2018_HJqUtdOaZ	ENRICHMENT OF FEATURES FOR CLASSIFICATION USING AN OPTIMIZED LINEAR/NON-LINEAR COMBINATION OF INPUT FEATURES	Automatic classification of objects is one of the most important tasks in engineering and data mining applications. Although using more complex and advanced classifiers can help to improve the accuracy of classification systems, it can be done by analyzing data sets and their features for a particular...	rejected-papers	The presented method essentially builds a model that remaps features into a new space that optimizes nearest-neighbor classification. The model is a neural network, and the optimization is carried out through a genetic algorithm. Pros: - One major issue with neural network classification is that of a lack of explaina...	val	[ "rkbO-pIgf", "rkvIrecgG", "r1o4FsqgM" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "The paper presents a method for feature projection which uses a two level neural network like structure to generate new features from the input features. The weights of the NN like structure are optimised using a genetic search algorithm which optimises the cross-validation error of a nearest neighbor classifier. ...	[ 1, 3, 2 ]	[ 5, 4, 3 ]	[ "iclr_2018_HJqUtdOaZ", "iclr_2018_HJqUtdOaZ", "iclr_2018_HJqUtdOaZ" ]
iclr_2018_S1m6h21Cb	The Cramer Distance as a Solution to Biased Wasserstein Gradients	The Wasserstein probability metric has received much attention from the machine learning community. Unlike the Kullback-Leibler divergence, which strictly measures change in probability, the Wasserstein metric reflects the underlying geometry between outcomes. The value of being sensitive to this geometry has been demo...	rejected-papers	Pros: - The authors propose a new algorithm to train GAN based on Cramer distance arguing that this eases optimization compared to Wasserstein GAN. - Reviewers agree that the paper reads well and provides a good overview of the properties of divergence measures used for GAN training. Cons: - It is not clear how much ...	train	[ "SJrqRODeM", "B1tHGLTgG", "B1xzpQy-z", "Hy_hZL2WM", "S14Zi72ZG", "rJYu5XnbM", "Bk4m5X2bM", "S19g4lpAZ" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "public" ]	[ "The manuscript proposes to use the Cramer distance as a measure between distributions (acting as a loss) when optimizing\nan objective function using stochastic gradient descent (SGD). Cramer distance is a Bregman divergence and is a member of the Lp family of divergences. Here a \"distance\" means a symmetric di...	[ 5, 4, 7, -1, -1, -1, -1, -1 ]	[ 3, 5, 2, -1, -1, -1, -1, -1 ]	[ "iclr_2018_S1m6h21Cb", "iclr_2018_S1m6h21Cb", "iclr_2018_S1m6h21Cb", "S19g4lpAZ", "SJrqRODeM", "B1tHGLTgG", "B1xzpQy-z", "iclr_2018_S1m6h21Cb" ]
iclr_2018_SJahqJZAW	Stabilizing GAN Training with Multiple Random Projections	Training generative adversarial networks is unstable in high-dimensions as the true data distribution tends to be concentrated in a small fraction of the ambient space. The discriminator is then quickly able to classify nearly all generated samples as fake, leaving the generator without meaningful gradients and causing...	rejected-papers	The paper proposes to use multiple discriminators to stabilize the GAN training process. Additionally, the discriminators only see randomly projected real and generated samples. Some valid concerns raised by the reviewers which makes the paper weak: - Multiple discriminators have been tried before and the authors do ...	val	[ "r1rx-5Oxf", "BJARkptxz", "rkhnnvolz", "rkk7fo37G", "BkwO6iHGf", "ry0wsiSGz", "SygZiiBMM" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "\nThe paper proposes to stabilize GAN training by using an ensemble of discriminators, each workin on a random projection of the input data, to provide the training signal for the generator model.\n\nQ1: “In relation to “Theorem 3.1. … will produce samples from a distribution whose marginals along each of the proj...	[ 5, 3, 8, -1, -1, -1, -1 ]	[ 4, 5, 4, -1, -1, -1, -1 ]	[ "iclr_2018_SJahqJZAW", "iclr_2018_SJahqJZAW", "iclr_2018_SJahqJZAW", "iclr_2018_SJahqJZAW", "r1rx-5Oxf", "BJARkptxz", "rkhnnvolz" ]
iclr_2018_Hy7EPh10W	Novelty Detection with GAN	The ability of a classifier to recognize unknown inputs is important for many classification-based systems. We discuss the problem of simultaneous classification and novelty detection, i.e. determining whether an input is from the known set of classes and from which specific class, or from an unknown domain and does no...	rejected-papers	Pros: The paper aims to unify classification and novelty detection which is interesting and challenging. Cons: - The reviewers find that the work is incremental and contains heuristics. Reviewers find the repurposing of the fake logit in semi-supervised GAN discriminator for assigning novelty strange. - The experiment...	train	[ "H18Yvh7xG", "HkMvZzYez", "HkCfpG5xf", "Hy-6lhjgG", "BJZYcBsxf", "rJrVZgdlG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "public", "author", "public" ]	[ "This paper proposed a GAN to unify classification and novelty detection. The technical difficulty is acceptable, but there are several issues. First of all, the motivation is clearly given in the 1st paragraph of the introduction: \"In fact for such novel input the algorithm will produce erroneous output and class...	[ 4, 5, 6, -1, -1, -1 ]	[ 4, 4, 4, -1, -1, -1 ]	[ "iclr_2018_Hy7EPh10W", "iclr_2018_Hy7EPh10W", "iclr_2018_Hy7EPh10W", "BJZYcBsxf", "rJrVZgdlG", "iclr_2018_Hy7EPh10W" ]
iclr_2018_S1EfylZ0Z	Anomaly Detection with Generative Adversarial Networks	Many anomaly detection methods exist that perform well on low-dimensional problems however there is a notable lack of effective methods for high-dimensional spaces, such as images. Inspired by recent successes in deep learning we propose a novel approach to anomaly detection using generative adversarial networks. Given...	rejected-papers	The authors propose to detect anomaly based on its representation quality in the latent space of the GAN trained on valid samples. Reviewers agree that: - The proposed solution lacks novelty and similar approaches have been tried before. - The baselines presented in the paper are primitive and hence do not demonstrate...	val	[ "By9QpjXlf", "ryxTDKPlz", "BJ1oIDYlG", "By8xh4T7z", "H1-oo4aQf", "Hy3EoV6QM" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "In the paper, the authors proposed using GAN for anomaly detection.\nIn the method, we first train generator g_\\theta from a dataset consisting of only healthy data points.\nFor evaluating whether the data point x is anomalous or not, we search for a latent representation z such that x \\approx g_\\theta(z).\nIf ...	[ 4, 6, 4, -1, -1, -1 ]	[ 5, 4, 4, -1, -1, -1 ]	[ "iclr_2018_S1EfylZ0Z", "iclr_2018_S1EfylZ0Z", "iclr_2018_S1EfylZ0Z", "By9QpjXlf", "ryxTDKPlz", "BJ1oIDYlG" ]
iclr_2018_rJHcpW-CW	NOVEL AND EFFECTIVE PARALLEL MIX-GENERATOR GENERATIVE ADVERSARIAL NETWORKS	In this paper, we propose a mix-generator generative adversarial networks (PGAN) model that works in parallel by mixing multiple disjoint generators to approximate a complex real distribution. In our model, we propose an adjustment component that collects all the generated data points from the generators, learns the bo...	rejected-papers	The paper aims to address the mode collapse issue in GANs by training multiple generators and forcing them to be diverse. Reviewers agree that the proposed solution is not novel and has disadvantages such as increased parameters due to multiple generator models. The authors do not provide convincing arguments as to wh...	train	[ "HyqGENDgz", "ByyDCx9xf", "BkQh8t5gz", "B1n0E0vlf", "S19N17XlM" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "public" ]	[ "Overall, the writing is very confusing at points and needs some attention to make the paper clearer. I’m not entirely sure the authors understand the material particularly well, as I found some of the arguments and narrative confusing or just incorrect. I don’t really see any significant contribution here except “...	[ 3, 6, 5, -1, -1 ]	[ 5, 4, 4, -1, -1 ]	[ "iclr_2018_rJHcpW-CW", "iclr_2018_rJHcpW-CW", "iclr_2018_rJHcpW-CW", "S19N17XlM", "iclr_2018_rJHcpW-CW" ]
iclr_2018_S1FQEfZA-	A Classification-Based Perspective on GAN Distributions	A fundamental, and still largely unanswered, question in the context of Generative Adversarial Networks (GANs) is whether GANs are actually able to capture the key characteristics of the datasets they are trained on. The current approaches to examining this issue require significant human supervision, such as visual in...	rejected-papers	The paper proposes a new metric to measure GAN performance by training a classifier on the true labeled dataset and then comparing the distribution of the labels of the generated samples to the true label distribution. Reviewers find that the paper is well written but lacks novelty and is quite experimental does not pr...	train	[ "H1WAH_kxM", "BkTles9xM", "rJCxSIslz", "BJ-hES67G", "SJYJ1Ip7z", "SkMOSHp7M" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "Overall comments: Trying to shed light at comparison between different GAN variants, but the metrics introduced are not very novel, results are not comparable with prior work and older version of certain models are used (WGAN instead of Improved WGAN)\n\nSection 2.1: quantifying mode collapse\n* This section shoul...	[ 5, 6, 3, -1, -1, -1 ]	[ 5, 4, 4, -1, -1, -1 ]	[ "iclr_2018_S1FQEfZA-", "iclr_2018_S1FQEfZA-", "iclr_2018_S1FQEfZA-", "rJCxSIslz", "H1WAH_kxM", "BkTles9xM" ]
iclr_2018_B1tExikAW	LatentPoison -- Adversarial Attacks On The Latent Space	Robustness and security of machine learning (ML) systems are intertwined, wherein a non-robust ML system (classifiers, regressors, etc.) can be subject to attacks using a wide variety of exploits. With the advent of scalable deep learning methodologies, a lot of emphasis has been put on the robustness of supervised, un...	rejected-papers	The paper proposes to launch adversarial attacks in the latent space of VAE such that the minimal change in the latent representation leads to the decoder producing an image with class predictions altered. Given the pros/cons the paper in its current form falls short of acceptance. Pros: Reviewers agree that the pape...	train	[ "H1I-1LYxf", "HkCuu2YxG", "B1xzWeqgG", "rJUUQkn7f", "Sk9azy3mf", "BJ5KMJhmf" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "The idea is clearly stated (but lacks some details) and I enjoyed reading the paper. \n\nI understand the difference between [Kos+17] and the proposed scheme but I could not understand in which situation the proposed scheme works better. From the adversary's standpoint, it would be easier to manipulate inputs than...	[ 5, 3, 4, -1, -1, -1 ]	[ 3, 4, 4, -1, -1, -1 ]	[ "iclr_2018_B1tExikAW", "iclr_2018_B1tExikAW", "iclr_2018_B1tExikAW", "H1I-1LYxf", "HkCuu2YxG", "B1xzWeqgG" ]
iclr_2018_ryepFJbA-	On Convergence and Stability of GANs	We propose studying GAN training dynamics as regret minimization, which is in contrast to the popular view that there is consistent minimization of a divergence between real and generated distributions. We analyze the convergence of GAN training from this new point of view to understand why mode collapse happens. We hy...	rejected-papers	Pros: The proposed regularization for GAN training is interesting and simple to implement. Cons: - Reviewers agree that the methodology is incremental over the WGAN with gradient penalty and the modification is not well motivated. - Experimental results do not clearly demonstrate the benefits of the proposed algorithm...	train	[ "ByPQQOX1G", "SyYO2aIlG", "Hkd3vAUeG", "Bk9rWSD-f", "rJbz9QP-z", "H1HD-BDWf", "ryKUsoYbf", "S1wmdHPWf", "B1nRUuAgG", "S1GEAvq0Z", "S1EGL-uC-", "rJ91vcOCb", "ryIPRnuCb", "HkXuRauAZ", "HkxbyyKCb", "Sk8vLeK0b", "Hy1sFOsRW", "r184LvsCZ", "HyVsPP5CZ", "HkcJxbYRb", "r1nCXkK0Z", "...	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "public", "author", "author", "author", "author", "author", "author", "author", "author", "public", "public", "public", "public", "public", "public", "public...	[ "Summary\n========\nThe authors present a new regularization term, inspired from game theory, which encourages the discriminator's gradient to have a norm equal to one. This leads to reduce the number of local minima, so that the behavior of the optimization scheme gets closer to the optimization of a zero-sum game...	[ 5, 4, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 ]	[ 2, 5, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_ryepFJbA-", "iclr_2018_ryepFJbA-", "iclr_2018_ryepFJbA-", "SyYO2aIlG", "Hkd3vAUeG", "Bk9rWSD-f", "B1nRUuAgG", "ByPQQOX1G", "iclr_2018_ryepFJbA-", "HyVsPP5CZ", "ByD_wguCW", "rJxYq4uAZ", "S1yaH2dAb", "Bk-qS6_RW", "BJlRh0dC-", "r1nCXkK0Z", "r184LvsCZ", "S1GEAvq0Z", "iclr_...
iclr_2018_ry4SNTe0-	Improve Training Stability of Semi-supervised Generative Adversarial Networks with Collaborative Training	Improved generative adversarial network (Improved GAN) is a successful method of using generative adversarial models to solve the problem of semi-supervised learning. However, it suffers from the problem of unstable training. In this paper, we found that the instability is mostly due to the vanishing gradients on the g...	rejected-papers	The paper aims to combine Wasserstein GAN with Improved GAN framework for semi-supervised learning. The reviewers unanimously agree that: - the paper lacks novelty and such approaches have been tried before. - the approach does not make sufficient gains over the baselines and stronger baselines are missing. - the p...	test	[ "B1uXHzDeM", "SkaNEl9xM", "BJGtGM9eM" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "* Summary *\nThe paper addresses the instability of GAN training. More precisely, the authors aim at improving the stability of the semi-supervised version of GANs presented in [1] (IGAN for short) . The paper presents a novel architecture for training adversarial networks in a semi-supervised settings (Algorithm ...	[ 3, 2, 3 ]	[ 4, 4, 5 ]	[ "iclr_2018_ry4SNTe0-", "iclr_2018_ry4SNTe0-", "iclr_2018_ry4SNTe0-" ]
iclr_2018_By9iRkWA-	Phase Conductor on Multi-layered Attentions for Machine Comprehension	Attention models have been intensively studied to improve NLP tasks such as machine comprehension via both question-aware passage attention model and self-matching attention model. Our research proposes phase conductor (PhaseCond) for attention models in two meaningful ways. First, PhaseCond, an architecture of multi-l...	rejected-papers	Generally solid engineering work but a bit lacking in terms of novelty and some issues with clarity. At the end of the day the empirical gains are not sufficient for acceptance - the results are state-of-the-art relative to published work, but not in the top 10 based on the official leaderboard (not even at time of sub...	train	[ "HkFCIBhgf", "HyrDvKC1z", "B1s84WMlM", "Bkhb6wpXM", "BJVf3P67G", "HykAjPT7G", "By6zYD6mz" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "This paper introduces a fairly elaborate model for reading comprehension evaluated on the SQuAD dataset. The model is shown to improve on the published results but not as-of-submission leaderboard numbers.\n\nThe main weakness of the paper in my opinion is that the innovations seem to be incremental and not base...	[ 8, 5, 5, -1, -1, -1, -1 ]	[ 3, 5, 4, -1, -1, -1, -1 ]	[ "iclr_2018_By9iRkWA-", "iclr_2018_By9iRkWA-", "iclr_2018_By9iRkWA-", "HyrDvKC1z", "B1s84WMlM", "B1s84WMlM", "HkFCIBhgf" ]
iclr_2018_S1Q79heRW	Unsupervised Learning of Entailment-Vector Word Embeddings	Entailment vectors are a principled way to encode in a vector what information is known and what is unknown. They are designed to model relations where one vector should include all the information in another vector, called entailment. This paper investigates the unsupervised learning of entailment vectors for the se...	rejected-papers	Two knowledgeable and confident reviewers suggest rejection, while one not confident reviewer suggests acceptance. I agree with the confident reviewers. All reviewers also point out that the paper is confusingly written and difficult to understand.	train	[ "r1kr4BQgG", "SJ4HCiUgz", "BkjD4Eqxz", "ryK-BFqfM", "H1mMzY9Gf", "Sk_LeFqGf" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "I'm finding this paper really difficult to understand. The introduction is very abstract, and it is hard for me to understand the model as it is explained at the moment. Could the authors please clarify, perhaps in more algorithmic terms, how the model works?\n\nAs for the evaluation, BLESS is a nice dataset, but ...	[ 3, 7, 3, -1, -1, -1 ]	[ 5, 3, 5, -1, -1, -1 ]	[ "iclr_2018_S1Q79heRW", "iclr_2018_S1Q79heRW", "iclr_2018_S1Q79heRW", "r1kr4BQgG", "SJ4HCiUgz", "BkjD4Eqxz" ]
iclr_2018_ryOG3fWCW	Model Specialization for Inference Via End-to-End Distillation, Pruning, and Cascades	The availability of general-purpose reference and benchmark datasets such as ImageNet have spurred the development of general-purpose popular reference model architectures and pre-trained weights. However, in practice, neural net- works are often employed to perform specific, more restrictive tasks, t...	rejected-papers	This paper does not meet the bar for ICLR - neither in terms of the quality of the write-up, nor in experimental design. The two confident reviewers agree to reject the paper, the weak accept comes from a less confident reviewer who did not write a good review at all. The rebuttal does not change this assessment.	train	[ "rJ6qTo7gz", "r1wK-mFlM", "HJtb_2teM" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "The paper presents an approach to do task aware distillation, task-specific pruning and specialized cascades. The main result is that such methods can yield smaller, efficient and sometimes more accurate models.\n\nThe proposed approach is simple and easy to understand. The task aware distillation relies on the av...	[ 6, 4, 3 ]	[ 3, 4, 4 ]	[ "iclr_2018_ryOG3fWCW", "iclr_2018_ryOG3fWCW", "iclr_2018_ryOG3fWCW" ]
iclr_2018_rJ8rHkWRb	A Simple Fully Connected Network for Composing Word Embeddings from Characters	This work introduces a simple network for producing character aware word embeddings. Position agnostic and position aware character embeddings are combined to produce an embedding vector for each word. The learned word representations are shown to be very sparse and facilitate improved results on language modeling task...	rejected-papers	The paper presents yet another approach for modeling words based on their characters. Unfortunately the authors do not compare properly to previous approaches and the idea is very incremental.	val	[ "By7uW7Pef", "HkDiq0Flf", "Byp-dy9gG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "The authors propose a neural network architecture which takes the characters of a word as input along with their positions, and output a word embedding. They then use these as inputs to a GRU language model, which is evaluated on two medium size data sets made from a series of novels and the Project Gutenberg Cana...	[ 3, 5, 4 ]	[ 4, 4, 5 ]	[ "iclr_2018_rJ8rHkWRb", "iclr_2018_rJ8rHkWRb", "iclr_2018_rJ8rHkWRb" ]
iclr_2018_rkYgAJWCZ	One-shot and few-shot learning of word embeddings	Standard deep learning systems require thousands or millions of examples to learn a concept, and cannot integrate new concepts easily. By contrast, humans have an incredible ability to do one-shot or few-shot learning. For instance, from just hearing a word used in a sentence, humans can infer a great deal about it, by...	rejected-papers	The paper is looking at an interesting problem, but it seems too early. The approach requires training a new language model from scratch for each new word, rendering it completely impractical for real use. The main evaluation therefore only considers four words - "bonuses", "explained", "marketers", "strategist" (expa...	train	[ "Sk9dBhUlG", "HJnrNAtlG", "Sybz8F9eG", "B1rxDNtmG", "r1i_IEtmG", "S1fm8Vt7z", "ByDSg2Ggz", "rJEcBKfxG", "rJcKVpa1f" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "public", "author", "public" ]	[ "I am highly sympathetic to the goals of this paper, and the authors do a good job of contrasting human learning with current deep learning systems, arguing that the lack of a mechanism for few-shot learning in such systems is a barrier to applying them in realistic scenarios. However, the main evaluation only cons...	[ 4, 3, 4, -1, -1, -1, -1, -1, -1 ]	[ 4, 4, 4, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_rkYgAJWCZ", "iclr_2018_rkYgAJWCZ", "iclr_2018_rkYgAJWCZ", "Sk9dBhUlG", "HJnrNAtlG", "Sybz8F9eG", "rJEcBKfxG", "rJcKVpa1f", "iclr_2018_rkYgAJWCZ" ]
iclr_2018_HJw8fAgA-	Learning Dynamic State Abstractions for Model-Based Reinforcement Learning	A key challenge in model-based reinforcement learning (RL) is to synthesize computationally efficient and accurate environment models. We show that carefully designed models that learn predictive and compact state representations, also called state-space models, substantially reduce the computational costs for predicti...	rejected-papers	There was quite a bit of discussion about this paper but in the end the majority felt that, though the paper is interesting, the results are too limited and more needs to be done for publication. PROS: 1. Good comparison of state space model variations 2. Good writing (perhaps a bit dense in places) 3. Promising resul...	train	[ "HyV_TbIBf", "SyfTyqXSM", "H1KbSmYeM", "BkJknsz-f", "BkCqRjmZz", "B106AfgfG", "HyFH0GgGf", "HkDEpzlGz", "r1FwqfeGG" ]	[ "author", "public", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "Would the author of the comment elaborate on their objection? \n\nThe title is justified in our opinion; we use the term \"dynamic state abstraction\" to emphasize the following:\n- we learn state presentations that are more compact than the the raw observations at a single time step, hence they constitute \"abst...	[ -1, -1, 6, 5, 8, -1, -1, -1, -1 ]	[ -1, -1, 4, 4, 4, -1, -1, -1, -1 ]	[ "SyfTyqXSM", "iclr_2018_HJw8fAgA-", "iclr_2018_HJw8fAgA-", "iclr_2018_HJw8fAgA-", "iclr_2018_HJw8fAgA-", "H1KbSmYeM", "HkDEpzlGz", "BkJknsz-f", "BkCqRjmZz" ]
iclr_2018_SJky6Ry0W	Learning Independent Causal Mechanisms	Independent causal mechanisms are a central concept in the study of causality with implications for machine learning tasks. In this work we develop an algorithm to recover a set of (inverse) independent mechanisms relating a distribution transformed by the mechanisms to a reference distribution. ...	rejected-papers	PROS: 1. All the reviewers thought that the work was interesting and showed promise 2. The paper is relatively well written CONS: 1. Limited experimental evaluation (just MNIST) The reviewers were all really on the fence about this but in the end felt that while the idea was a good one and the authors were responsive...	train	[ "rJAS034ez", "S12z02uez", "SkiVnWtxM", "Hy0bIIFQf", "ryQnSLtXM", "rkUzBUKXz", "rJR1r8FQf", "SkzjmUKXG", "HypuI-dxG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author" ]	[ "This paper presents a framework to recover a set of independent mechanisms. In order to do so it uses a set of experts each one made out of a GAN.\n\nMy main concern with this work is that I don't see any mechanism in the framework that prevents an expert (or few of them) to win all examples except its own learni...	[ 6, 5, 5, -1, -1, -1, -1, -1, -1 ]	[ 4, 4, 4, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_SJky6Ry0W", "iclr_2018_SJky6Ry0W", "iclr_2018_SJky6Ry0W", "iclr_2018_SJky6Ry0W", "rJAS034ez", "S12z02uez", "S12z02uez", "SkiVnWtxM", "iclr_2018_SJky6Ry0W" ]
iclr_2018_HkepKG-Rb	A Semantic Loss Function for Deep Learning with Symbolic Knowledge	This paper develops a novel methodology for using symbolic knowledge in deep learning. From first principles, we derive a semantic loss function that bridges between neural output vectors and logical constraints. This loss function captures how close the neural network is to satisfying the constraints on its output. An...	rejected-papers	This one was really on the fence. After some additional rounds of discussion post-rebuttal with the reviewers I think the general consensus is that it's a good paper and almost there but not quite ready for acceptance at this time. A detailed list of issues and concerns below. PROS: 1. good idea: an additional loss ...	train	[ "SkRvF__xf", "ByEQXA5lM", "SJJw0N0eM", "S1cu8ZLmf", "BJYV8WUmG", "Syd2rWUQM" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "SUMMARY \n\nThe paper proposes a new form of regularization utilizing logical constraints. The semantic loss function is built on the exploitation of symbolic knowledge extracted from data and connecting the logical constraints to the outputs of a neural network. The use of Boolean logic as a constraint provides a...	[ 7, 5, 4, -1, -1, -1 ]	[ 3, 3, 4, -1, -1, -1 ]	[ "iclr_2018_HkepKG-Rb", "iclr_2018_HkepKG-Rb", "iclr_2018_HkepKG-Rb", "SkRvF__xf", "ByEQXA5lM", "SJJw0N0eM" ]
iclr_2018_HJnQJXbC-	AMPNet: Asynchronous Model-Parallel Training for Dynamic Neural Networks	New types of compute hardware in development and entering the market hold the promise of revolutionizing deep learning in a manner as profound as GPUs. However, existing software frameworks and training algorithms for deep learning have yet to evolve to fully leverage the capability of the new wave of silicon. I...	rejected-papers	The authors propose a system for asynchronous, model-parallel training, suitable for dynamic neural networks. To summarize the reviewers: PROS: 1. Paper contrasts well with existing work. 2. Positive results on dynamic neural network problems. 3. Well written and clear CONS: 1. Some concern about extrapolations/esti...	train	[ "B1vCBbYlz", "HJwWcV8gz", "HJKXoRdgf", "HkGay76mG", "BkBqKCvMz", "r1Gy453ZM", "Symd8cB-G", "HyWWIcHbf", "HJlT49r-M" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "official_reviewer", "author", "author", "author" ]	[ "This paper proposes new direction for asynchronous training. While many synchronous and asynchronous approaches for data parallelism have been proposed and implemented in the past, the space of asynchronous model parallelism hasn't really been explored before. This paper discusses an implementation of this approac...	[ 6, 6, 4, -1, -1, -1, -1, -1, -1 ]	[ 5, 4, 5, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_HJnQJXbC-", "iclr_2018_HJnQJXbC-", "iclr_2018_HJnQJXbC-", "iclr_2018_HJnQJXbC-", "r1Gy453ZM", "HyWWIcHbf", "HJwWcV8gz", "HJKXoRdgf", "B1vCBbYlz" ]
iclr_2018_B1CQGfZ0b	Learning to select examples for program synthesis	Program synthesis is a class of regression problems where one seeks a solution, in the form of a source-code program, that maps the inputs to their corresponding outputs exactly. Due to its precise and combinatorial nature, it is commonly formulated as a constraint satisfaction problem, where input-output examples are ...	rejected-papers	The reviewers were largely agreed that the paper presented an interesting idea and has potential but needs a better empirical evaluation. It seems that the authors largely agree and are working to improve it. PROS: 1. Improving the speed of program synthesis is a useful problem 2. Good treatment of related work, e.g....	train	[ "SJC_Polgz", "Bycm6ytgf", "By8NGl0xG", "Syz7_waXf", "BycOZvTXf", "SkzWAUTQG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "The paper proposes a method for identifying representative examples for program\nsynthesis to increase the scalability of existing constraint programming\nsolutions. The authors present their approach and evaluate it empirically.\n\nThe proposed approach is interesting, but I feel that the experimental section\ndo...	[ 4, 5, 5, -1, -1, -1 ]	[ 4, 4, 3, -1, -1, -1 ]	[ "iclr_2018_B1CQGfZ0b", "iclr_2018_B1CQGfZ0b", "iclr_2018_B1CQGfZ0b", "SJC_Polgz", "Bycm6ytgf", "By8NGl0xG" ]
iclr_2018_r1kjEuHpZ	Learning Less-Overlapping Representations	In representation learning (RL), how to make the learned representations easy to interpret and less overfitted to training data are two important but challenging issues. To address these problems, we study a new type of regularization approach that encourages the supports of weight vectors in RL models to have small ov...	rejected-papers	Each of the reviewers had a slightly different set of issues with this paper but here is an attempt at a summary: PROS: 1. Paper is mostly clear and well structured. CONS: 1. Lack of novelty 2. Unsupported claims 3. Questionable methodology (using dropout confounds the goal of the experiment) The authors did not sub...	train	[ "B1taBfmlG", "BJ9J8G_ez", "ByL47G5lM" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "Summary\nThe paper introduces a matrix regularizer to simultaneously induce both sparsity and (approximate) orthogonality. The definition of the regularizer mostly relies on the previous proposal from Xie et al. 2017b, to which a weighted L1 term is added.\nThe regularizer aims at reducing overlap among the lear...	[ 5, 4, 3 ]	[ 4, 4, 5 ]	[ "iclr_2018_r1kjEuHpZ", "iclr_2018_r1kjEuHpZ", "iclr_2018_r1kjEuHpZ" ]
iclr_2018_SJdCUMZAW	Data-efficient Deep Reinforcement Learning for Dexterous Manipulation	Grasping an object and precisely stacking it on another is a difficult task for traditional robotic control or hand-engineered approaches. Here we examine the problem in simulation and provide techniques aimed at solving it via deep reinforcement learning. We introduce two straightforward extensions to the Deep Determi...	rejected-papers	The reviewers were quite unanimous in their assessment of this paper. PROS: 1. The paper is relatively clear and the approach makes sense 2. The paper presents and evaluates a collection of approaches to speed learning of policies for manipulation tasks. 3. Improving the data efficiency of learning algorithms and enab...	train	[ "SJVDtoHef", "SyFsE_Def", "SkHZuZqxf", "SJEzPorez" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "I already reviewed this paper for R:SS 2017. There were no significant updates in this version, see my largely identical detailed comment in \"Official Comment\"\n\nQuality\n======\nThe proposed approaches make sense but it is unclear how task specific they are.\n\nClarity\n=====\nThe paper reads well. The authors...	[ 4, 2, 3, -1 ]	[ 4, 5, 4, -1 ]	[ "iclr_2018_SJdCUMZAW", "iclr_2018_SJdCUMZAW", "iclr_2018_SJdCUMZAW", "iclr_2018_SJdCUMZAW" ]
iclr_2018_H1kMMmb0-	Sequential Coordination of Deep Models for Learning Visual Arithmetic	Achieving machine intelligence requires a smooth integration of perception and reasoning, yet models developed to date tend to specialize in one or the other; sophisticated manipulation of symbols acquired from rich perceptual spaces has so far proved elusive. Consider a visual arithmetic task, where the goal is to car...	rejected-papers	The consensus among the reviewers is that this paper is not quite ready for publication for reasons I will summarize in more detail below. However, I think there are some things that are really nice about this approach, and worth calling out: PROS: 1. the idea of tackling tasks broadly all the way from perception th...	train	[ "ByFXl7Def", "BkQXYLhgz", "BJzWfyTlf", "SkqQIMvMf", "rkcJUMwGf", "H1njHMvzG", "SkoIrMwfG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "Summary: This work is a variant of previous work (Zaremba et al. 2016) that enables the use of (noisy) operators that invoke pre-trained neural networks and is trained with Actor-Critic. In this regard it lacks a bit of originality. The quality of the experimental evaluation is not great. The clarity of the paper ...	[ 4, 3, 2, -1, -1, -1, -1 ]	[ 4, 4, 4, -1, -1, -1, -1 ]	[ "iclr_2018_H1kMMmb0-", "iclr_2018_H1kMMmb0-", "iclr_2018_H1kMMmb0-", "ByFXl7Def", "ByFXl7Def", "BkQXYLhgz", "BJzWfyTlf" ]
iclr_2018_BkIkkseAZ	Theoretical properties of the global optimizer of two-layer Neural Network	In this paper, we study the problem of optimizing a two-layer artificial neural network that best fits a training dataset. We look at this problem in the setting where the number of parameters is greater than the number of sampled points. We show that for a wide class of differentiable activation functions (this class ...	rejected-papers	Understanding the quality of the solutions found by gradient descent for optimizing deep nets is certainly an important area of research. The reviewers found several intermediate results to be interesting. At the same time, the reviewers unanimously have pointed out various technical aspects of the paper that are uncl...	train	[ "SyQTA31bG", "ByASB9UEG", "BJUmm5_lz", "SJccyr0-M", "rkvgtaimf", "SyqV2dWfz", "rJSis_bfz", "r1XDiO-GG", "r1FKsfwWz", "ryRVo4QeM", "rkQ3TFMxG", "SJMDtxGlz", "rypGH4bgG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "author", "official_reviewer" ]	[ "The paper studies the theoretical properties of the two-layer neural networks. \n\nTo summarize the result, let's use the theta to denote the layer closer to the label, and W to denote the layer closer to the data. \n\nThe paper shows that \na) if W is fixed, then with respect to the randomness of the data, with p...	[ 4, -1, 7, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1 ]	[ 5, -1, 5, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_BkIkkseAZ", "rJSis_bfz", "iclr_2018_BkIkkseAZ", "iclr_2018_BkIkkseAZ", "SJccyr0-M", "SyQTA31bG", "r1XDiO-GG", "BJUmm5_lz", "SyQTA31bG", "rkQ3TFMxG", "SJMDtxGlz", "rypGH4bgG", "iclr_2018_BkIkkseAZ" ]
iclr_2018_ryCM8zWRb	Recurrent Neural Networks with Top-k Gains for Session-based Recommendations	RNNs have been shown to be excellent models for sequential data and in particular for session-based user behavior. The use of RNNs provides impressive performance benefits over classical methods in session-based recommendations. In this work we introduce a novel ranking loss function tailored for RNNs in recommendation...	rejected-papers	While the use of RNNs for building session-based recommender systems is certainly an important class of applications, the main strength of the paper is to propose and benchmark practical modifications to prior RNN-based systems that lead to performance improvements. The reviewers have pointed out that the writing in th...	val	[ "ryqETl9gG", "S1d1eXqlM", "r1QqAe3lG", "B1Qwgzlff", "B1VZezgff", "Hy35efeMz" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "This is an interesting paper that analyzes existing loss functions for session-based recommendations. Based on the result of these analysis the authors propose two novel losses functions which add a weighting to existing ranking-based loss functions. These novelties are meant to improve issues related to vanishing...	[ 8, 4, 6, -1, -1, -1 ]	[ 4, 5, 5, -1, -1, -1 ]	[ "iclr_2018_ryCM8zWRb", "iclr_2018_ryCM8zWRb", "iclr_2018_ryCM8zWRb", "S1d1eXqlM", "r1QqAe3lG", "ryqETl9gG" ]
iclr_2018_r1saNM-RW	Small Coresets to Represent Large Training Data for Support Vector Machines	Support Vector Machines (SVMs) are one of the most popular algorithms for classification and regression analysis. Despite their popularity, even efficient implementations have proven to be computationally expensive to train at a large-scale, especially in streaming settings. In this paper, we propose a novel coreset co...	rejected-papers	While the paper shows some encouraging results for scaling up SVMs using coreset methods, it has fallen short of making a fully convincing case, particularly given the amount of intense interest in this topic back in the heydey of kernel methods. When it comes to scalability, it has become the norm now to benchmark res...	train	[ "BylLVbdNG", "H11vg1wVf", "Byu50uOxf", "BJu6VdYlf", "rkydZLAef", "ByibM2BMz", "B1vBW3SGz", "Sk3SxYn-G", "HJwWeF3bM", "rJoTyFh-G", "SkwxyY2bM" ]	[ "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author" ]	[ "Thank you for the additional consideration.\n\n1) Regarding the offline running time of our algorithm, we include below the response that we had posted earlier regarding the runtime comparisons. In short, our algorithm, unlike prior approaches, can be applied to streaming settings where it may not be possible to...	[ -1, -1, 5, 7, 5, -1, -1, -1, -1, -1, -1 ]	[ -1, -1, 3, 3, 4, -1, -1, -1, -1, -1, -1 ]	[ "H11vg1wVf", "B1vBW3SGz", "iclr_2018_r1saNM-RW", "iclr_2018_r1saNM-RW", "iclr_2018_r1saNM-RW", "rkydZLAef", "iclr_2018_r1saNM-RW", "Byu50uOxf", "BJu6VdYlf", "rkydZLAef", "iclr_2018_r1saNM-RW" ]
iclr_2018_H1U_af-0-	Quadrature-based features for kernel approximation	We consider the problem of improving kernel approximation via feature maps. These maps arise as Monte Carlo approximation to integral representations of kernel functions and scale up kernel methods for larger datasets. We propose to use more efficient numerical integration technique to obtain better estimates of the in...	rejected-papers	This an interesting new contribution to construction of random features for approximating kernel functions. While the empirical results look promising, the reviewers have raised concerns about not having insights into why the approach is more effective; the exposition of the quadrature method is difficult to follow; a...	train	[ "H1--71dlz", "BkpB7yqxz", "SyGYH-ieG", "BymT16sXz", "SyjTxTsmz", "S1D-gTjmf" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "The paper proposes to improve the kernel approximation of random features by using quadratures, in particular, stochastic spherical-radial rules. The quadrature rules have smaller variance given the same number of random features, and experiments show its reconstruction error and classification accuracies are bett...	[ 4, 7, 6, -1, -1, -1 ]	[ 3, 5, 4, -1, -1, -1 ]	[ "iclr_2018_H1U_af-0-", "iclr_2018_H1U_af-0-", "iclr_2018_H1U_af-0-", "SyGYH-ieG", "H1--71dlz", "BkpB7yqxz" ]
iclr_2018_HJBhEMbRb	A Spectral Approach to Generalization and Optimization in Neural Networks	The recent success of deep neural networks stems from their ability to generalize well on real data; however, Zhang et al. have observed that neural networks can easily overfit random labels. This observation demonstrates that with the existing theory, we cannot adequately explain why gradient methods can find generali...	rejected-papers	Understanding the generalization behavior of deep networks is certainly an open problem. While this paper appears to develop some interesting new Fourier-based methods in this direction, the analysis in its current form is currently too restrictive, with somewhat limited empirical support, to broadly appeal to the ICLR...	train	[ "rkcAW6tJG", "SJk182OlM", "H1Mweadlz", "S1Zg-PTQG", "B1f8kP6QM", "BJg_JQeXz", "ryglRAbMG", "HkpNpRbMf", "SJhIn0bfM", "ByHaYRulf", "HJ815-Lxz", "HJ1KekUef", "ry3-q3Xez", "r1I4--WxG", "rJOFw1u1z" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "public", "author", "author", "author", "author", "public", "author", "public", "author", "public" ]	[ "Deep neural networks have found great success in various applications. This paper presents a theoretical analysis for 2-layer neural networks (NNs) through a spectral approach. Specifically, the authors develop a Fourier-based generalization bound. Based on this, the authors show that the bandwidth, Fourier l_1 no...	[ 6, 6, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 ]	[ 3, 3, 4, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_HJBhEMbRb", "iclr_2018_HJBhEMbRb", "iclr_2018_HJBhEMbRb", "BJg_JQeXz", "iclr_2018_HJBhEMbRb", "iclr_2018_HJBhEMbRb", "rkcAW6tJG", "SJk182OlM", "H1Mweadlz", "HJ815-Lxz", "HJ1KekUef", "ry3-q3Xez", "r1I4--WxG", "rJOFw1u1z", "iclr_2018_HJBhEMbRb" ]
iclr_2018_SJ8M9yup-	On Optimality Conditions for Auto-Encoder Signal Recovery	Auto-Encoders are unsupervised models that aim to learn patterns from observed data by minimizing a reconstruction cost. The useful representations learned are often found to be sparse and distributed. On the other hand, compressed sensing and sparse coding assume a data generating process, where the observed data is ...	rejected-papers	- The paper is overall difficult to read and would benefit from a revised presentation. - The practical relevance of the recovery conditions and algorithmic consequences of the work is not sufficiently clear or convincing.	train	[ "HySa8MQgz", "B1NjQYOeG", "HkQOWPieM", "r1Nk9t2Xz", "BkNZsY27f", "r1bwcKhQz" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "Summary\nThe paper studies recovery guarantees within the context of auto-encoders. Assuming a noise-corrupted linear model for the inputs x's, the paper looks at some sufficient properties (e.g., over the generating dictionary denoted by W) to recover the true underlying sparse signals (denoted by h). Several s...	[ 4, 5, 5, -1, -1, -1 ]	[ 3, 4, 4, -1, -1, -1 ]	[ "iclr_2018_SJ8M9yup-", "iclr_2018_SJ8M9yup-", "iclr_2018_SJ8M9yup-", "HkQOWPieM", "HySa8MQgz", "B1NjQYOeG" ]
iclr_2018_SJu63o10b	UNSUPERVISED METRIC LEARNING VIA NONLINEAR FEATURE SPACE TRANSFORMATIONS	In this paper, we propose a nonlinear unsupervised metric learning framework to boost of the performance of clustering algorithms. Under our framework, nonlinear distance metric learning and manifold embedding are integrated and conducted simultaneously to increase the natural separations among data samples. The metric...	rejected-papers	The paper is well written overall. However, the algorithmic framework has limited novelty and the reviewers unanimously are unconvinced by experimental results showing marginal improvements on smallish UCI datasets.	train	[ "HJAY2L-ez", "BJfgoy9xz", "rkX795cez" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "This paper proposed an unsupervised metric learning method, which is designed for clustering and cannot be used for other problems. The authors argued that unsupervised metric learning should not be a pre-processing method for the following clustering method due to the lack of any similarity/dissimilarity constrai...	[ 6, 4, 4 ]	[ 4, 5, 4 ]	[ "iclr_2018_SJu63o10b", "iclr_2018_SJu63o10b", "iclr_2018_SJu63o10b" ]
iclr_2018_SJDYgPgCZ	Understanding Local Minima in Neural Networks by Loss Surface Decomposition	To provide principled ways of designing proper Deep Neural Network (DNN) models, it is essential to understand the loss surface of DNNs under realistic assumptions. We introduce interesting aspects for understanding the local minima and overall structure of the loss surface. The parameter domain of the loss surface can...	rejected-papers	The reviewers are unanimous in their opinion that the theoretical results in this paper are of limited novelty and significance. Several parts of the paper are not presented clearly enough. As such the paper is not ready for ICLR-2018 acceptance.	train	[ "HJfKMWtxz", "HJ_5MStgf", "B1kVUQjxM" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "This paper proposes to study the loss surfaces of neural networks with ReLU activations by viewing the loss surface as a sum of piecewise linear functions at each point in parameter space, i.e. one piecewise linear function per sample. The main result is that every local minimum of the total surface is a global mi...	[ 4, 5, 4 ]	[ 4, 4, 4 ]	[ "iclr_2018_SJDYgPgCZ", "iclr_2018_SJDYgPgCZ", "iclr_2018_SJDYgPgCZ" ]
iclr_2018_BJgd7m0xRZ	Unsupervised Adversarial Anomaly Detection using One-Class Support Vector Machines	Anomaly detection discovers regular patterns in unlabeled data and identifies the non-conforming data points, which in some cases are the result of malicious attacks by adversaries. Learners such as One-Class Support Vector Machines (OCSVMs) have been successfully in anomaly detection, yet their performance may degrade...	rejected-papers	The reviewers have unanimously expressed concerns about clarity, novelty, sound theoretical justification and intuitive motivation of the proposed approach.	test	[ "ByZrbWcxG", "BJLMRY2gG", "SkrFXoAef" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "The authors propose a defense against attacks on the security of one-class SVM based anonaly detectors. The core idea is to perform a random projection of the data (which is supposed to decrease the impact from adversarial distortions). The approach is empirically tested on the following data: MNIST, CIFAR, and SV...	[ 4, 4, 4 ]	[ 4, 4, 4 ]	[ "iclr_2018_BJgd7m0xRZ", "iclr_2018_BJgd7m0xRZ", "iclr_2018_BJgd7m0xRZ" ]
iclr_2018_HyiRazbRb	Demystifying overcomplete nonlinear auto-encoders: fast SGD convergence towards sparse representation from random initialization	Auto-encoders are commonly used for unsupervised representation learning and for pre-training deeper neural networks. When its activation function is linear and the encoding dimension (width of hidden layer) is smaller than the input dimension, it is well known that auto-encoder is optimized to learn the principa...	rejected-papers	The reviewers have unanimously expressed strong concerns about the technical correctness of the theoretical results in the paper. The paper should be carefully revised and checked for technical errors. In its current form, the paper is not suitable for acceptance at ICLR 2018.	train	[ "HyutwEMJG", "HkErJ5eez", "SJyMoI5gG", "H1vdfKpXG", "rJwXE9amz", "rkofl9aXM", "H1wvdY6mz" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "The authors study the convergence of a procedure for learning\nan autoencoder with a ReLu non-linearity. The procedure is akin\nto stochastic gradient descent, with some parameters updated at\neach iteration in a manner that performs optimization with respect\nto the population risk.\n\nThe autoencoders that they...	[ 2, 3, 2, -1, -1, -1, -1 ]	[ 4, 3, 4, -1, -1, -1, -1 ]	[ "iclr_2018_HyiRazbRb", "iclr_2018_HyiRazbRb", "iclr_2018_HyiRazbRb", "SJyMoI5gG", "iclr_2018_HyiRazbRb", "HyutwEMJG", "HkErJ5eez" ]
iclr_2018_rJSr0GZR-	Learning Priors for Adversarial Autoencoders	Most deep latent factor models choose simple priors for simplicity, tractability or not knowing what prior to use. Recent studies show that the choice of the prior may have a profound effect on the expressiveness of the model, especially when its generative network has limited capacity. In this paper,...	rejected-papers	The paper proposes learning the prior for AAEs by training a code-generator that is seeded by the standard Gaussian distribution and whose output is taken as the prior. The code generator is trained by minimizing the GAN loss b/w the distribution coming out of the decoder and the real image distribution. The paper also...	train	[ "ByzPtktlM", "BkD44d9gM", "ByjrTO5ef", "H1csCkCmz", "ryz-A1CXz", "HkKhMOgEM", "Hk2EakRmf", "SJvH3J0XM", "SkCykNYCb" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "public" ]	[ "This paper proposes an interesting idea--to learn a flexible prior from data by maximizing data likelihood.\n\nIt seems that in the prior improvement stage, what you do is training a GAN with CG+dec as the generator while D_I as the discriminator (since you also update dec at the prior improvement stage). So it ca...	[ 6, 5, 6, -1, -1, -1, -1, -1, -1 ]	[ 3, 3, 4, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_rJSr0GZR-", "iclr_2018_rJSr0GZR-", "iclr_2018_rJSr0GZR-", "SkCykNYCb", "ByzPtktlM", "Hk2EakRmf", "BkD44d9gM", "ByjrTO5ef", "iclr_2018_rJSr0GZR-" ]
iclr_2018_HyI6s40a-	Towards Safe Deep Learning: Unsupervised Defense Against Generic Adversarial Attacks	Recent advances in adversarial Deep Learning (DL) have opened up a new and largely unexplored surface for malicious attacks jeopardizing the integrity of autonomous DL systems. We introduce a novel automated countermeasure called Parallel Checkpointing Learners (PCL) to thwart the potential adversarial attacks and sign...	rejected-papers	The paper proposes a method to detect and correct adversarial examples at the input stage (using a sparse coding based model) and/or at a hidden layer (using a GMM). These detector/corrector models are trained using only the natural examples. While the proposed method is interesting and has some novelty wrt to the spec...	train	[ "rJ7exuPgM", "SJHkBN_xM", "HkkqUpk-f", "BJ9P82pmz", "Hklf_pYzf", "rJL6vTYMf", "H1R6UTKzM", "rkSaXaKMz" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "This paper present a method for detecting adversarial examples in a deep learning classification setting. The idea is to characterize the latent feature space (a function of inputs) as observed vs unobserved, and use a module to fit a 'cluster-aware' loss that aims to cluster similar classes tighter in the latent...	[ 5, 7, 3, -1, -1, -1, -1, -1 ]	[ 3, 3, 5, -1, -1, -1, -1, -1 ]	[ "iclr_2018_HyI6s40a-", "iclr_2018_HyI6s40a-", "iclr_2018_HyI6s40a-", "rkSaXaKMz", "SJHkBN_xM", "rJ7exuPgM", "SJHkBN_xM", "HkkqUpk-f" ]
iclr_2018_ryZERzWCZ	The Information-Autoencoding Family: A Lagrangian Perspective on Latent Variable Generative Modeling	A variety of learning objectives have been recently proposed for training generative models. We show that many of them, including InfoGAN, ALI/BiGAN, ALICE, CycleGAN, VAE, β-VAE, adversarial autoencoders, AVB, and InfoVAE, are Lagrangian duals of the same primal optimization problem. This generalization reveals the imp...	rejected-papers	The paper provides a constrained mutual information objective function whose Lagrangian dual covers several existing generative models. However reviewers are not convinced of the significance or usefulness of the proposed unifying framework (at least from the way results are presented currently in the paper). Authors h...	val	[ "S1ufxZqlG", "SkugmHtgf", "BJ8bKuOlM", "B1A1_t67z", "SJ2PZA-XM", "BycXcabXz", "rkckcaWXM", "HJqtmElmf" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "official_reviewer", "author", "author", "author" ]	[ "EDIT: I have read the authors' rebuttals and other reviews. My opinion has not been changed. I recommend the authors significantly revise their work, streamlining the narrative and making clear what problems and solutions they solve. While I enjoy the perspective of unifying various paths, it's unclear what insigh...	[ 4, 5, 6, -1, -1, -1, -1, -1 ]	[ 4, 4, 4, -1, -1, -1, -1, -1 ]	[ "iclr_2018_ryZERzWCZ", "iclr_2018_ryZERzWCZ", "iclr_2018_ryZERzWCZ", "SJ2PZA-XM", "BycXcabXz", "BJ8bKuOlM", "SkugmHtgf", "S1ufxZqlG" ]
iclr_2018_H1wt9x-RW	Interpretable and Pedagogical Examples	Teachers intentionally pick the most informative examples to show their students. However, if the teacher and student are neural networks, the examples that the teacher network learns to give, although effective at teaching the student, are typically uninterpretable. We show that training the student and teacher iterat...	rejected-papers	The paper proposes iterative training strategies for learning teacher and student models. They show how iterative training can lead to interpretable strategies over joint training on multiple datasets. All the reviewers felt the idea was interesting, although, one of the reviewers had concerns about the experimentation...	train	[ "Bk8IzGblG", "Hk2pegqlf", "r1RtXlk-f", "B1U8nvY7G", "H1Et5DFmf", "BJYBqDFmG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "This is a well written paper on a compelling topic: how to train \"an automated teacher\" to use intuitive strategies that would also apply to humans. \n\nThe introduction is fairly strong, but this reviewer wishes that the authors would have come up with an intuitive example that illustrates why the strategy \"1...	[ 8, 8, 4, -1, -1, -1 ]	[ 3, 4, 3, -1, -1, -1 ]	[ "iclr_2018_H1wt9x-RW", "iclr_2018_H1wt9x-RW", "iclr_2018_H1wt9x-RW", "Hk2pegqlf", "Bk8IzGblG", "r1RtXlk-f" ]
iclr_2018_B13EC5u6W	Thinking like a machine — generating visual rationales through latent space optimization	Interpretability and small labelled datasets are key issues in the practical application of deep learning, particularly in areas such as medicine. In this paper, we present a semi-supervised technique that addresses both these issues simultaneously. We learn dense representations from large unlabelled image datasets, t...	rejected-papers	The paper proposes a semi-supervised method to make deep learning more interpretable and at the same time be accurate on small datasets. The main idea is to learn dense representations from unlabelled data and then use those for building classifiers on small datasets as well as generate visual explanations. The idea is...	test	[ "BJvBh8sEz", "HJ8fKmLVz", "SkjR3ZUNM", "r1MKh-INz", "rJIBvHSEz", "ByWcetHlG", "rygt6qdxM", "SkMSOTOlG", "S1Hw58XEz", "H1Qslp1XG", "BJY8gayXz", "r1QHxTJXM", "SJ2XQTJQf" ]	[ "author", "official_reviewer", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "Thank you for your reply - as per your request Table 2 has been updated to include some of our response to Reviewer 1 as a caption to help understand the table's contents. \n\n", "Thank you for updating the paper. I am satisfied with the changes.\n\nHowever, and as noted by the other reviewers, the description o...	[ -1, -1, -1, -1, -1, 4, 8, 7, -1, -1, -1, -1, -1 ]	[ -1, -1, -1, -1, -1, 3, 2, 4, -1, -1, -1, -1, -1 ]	[ "HJ8fKmLVz", "r1QHxTJXM", "rJIBvHSEz", "S1Hw58XEz", "BJY8gayXz", "iclr_2018_B13EC5u6W", "iclr_2018_B13EC5u6W", "iclr_2018_B13EC5u6W", "H1Qslp1XG", "ByWcetHlG", "rygt6qdxM", "SkMSOTOlG", "iclr_2018_B13EC5u6W" ]
iclr_2018_ByYPLJA6W	Distribution Regression Network	We introduce our Distribution Regression Network (DRN) which performs regression from input probability distributions to output probability distributions. Compared to existing methods, DRN learns with fewer model parameters and easily extends to multiple input and multiple output distributions. On synthetic and real-wo...	rejected-papers	The paper proposes a method to map input probability distributions to output probability distributions with few parameters. They show the efficacy of their method on synthetic and real stock data. After revision they seemed to have added another dataset, however, it is not carefully analyzed like the stock data. More r...	train	[ "B10sNZ9gM", "ByjbpsngM", "B1LsdVTlf", "HJtDnjDGG", "HJSgXjgGz", "SkS3fjgfG", "SJs8MoxfM", "Sym4GjlGM" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author" ]	[ "The paper considers distribution to distribution regression with MLPs. The authors use an energy function based approach. They test on a few problems, showing similar performance to other distribution to distribution alternatives, but requiring fewer parameters.\n\nThis seems to be a nice treatment of distributi...	[ 5, 7, 7, -1, -1, -1, -1, -1 ]	[ 4, 2, 4, -1, -1, -1, -1, -1 ]	[ "iclr_2018_ByYPLJA6W", "iclr_2018_ByYPLJA6W", "iclr_2018_ByYPLJA6W", "SkS3fjgfG", "B10sNZ9gM", "ByjbpsngM", "B1LsdVTlf", "iclr_2018_ByYPLJA6W" ]
iclr_2018_ry9tUX_6-	Entropy-SGD optimizes the prior of a PAC-Bayes bound: Data-dependent PAC-Bayes priors via differential privacy	We show that Entropy-SGD (Chaudhari et al., 2017), when viewed as a learning algorithm, optimizes a PAC-Bayes bound on the risk of a Gibbs (posterior) classifier, i.e., a randomized classifier obtained by a risk-sensitive perturbation of the weights of a learned classifier. Entropy-SGD works by optimizing the bound’s p...	rejected-papers	The paper proposes a new analysis of the optimization method called entropy-sgd which seemingly leads to more robust neural network classifiers. This is a very important problem if successful. The reviewers are on the fence with this paper. On the one hand they appreciate the direction and theoretical contribution, whi...	train	[ "Skza1ggrG", "Bk1HygxSM", "ryq2cm9xG", "r1dNqr9xf", "Hy0bdarZG", "Hk9z76OfG", "BkbCG6dzM", "SJMcMTOMz", "rJXPfp_GM" ]	[ "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "We revised our paper considerably over a month ago. We have since had a long back and forth conversation with AnonReviewer3 discussing the privacy approximation, which seems to have addressed their misgivings. \n\nWe would much appreciate it if you could update your reviews and/or score. ", "Dear AnonReviewer1,\...	[ -1, -1, 6, 6, 6, -1, -1, -1, -1 ]	[ -1, -1, 3, 3, 3, -1, -1, -1, -1 ]	[ "ryq2cm9xG", "r1dNqr9xf", "iclr_2018_ry9tUX_6-", "iclr_2018_ry9tUX_6-", "iclr_2018_ry9tUX_6-", "iclr_2018_ry9tUX_6-", "ryq2cm9xG", "r1dNqr9xf", "Hy0bdarZG" ]
iclr_2018_HJUOHGWRb	Contextual Explanation Networks	We introduce contextual explanation networks (CENs)---a class of models that learn to predict by generating and leveraging intermediate explanations. CENs are deep networks that generate parameters for context-specific probabilistic graphical models which are further used for prediction and play the role of explanation...	rejected-papers	The paper proposes a method to learn and explain simultaneously. The explanations are generated as part of the learning and in some sense come for free. It also goes the other way in that the explanations also help performance in simpler settings. Reviewers found the paper easy to follow and the idea has some value, ho...	test	[ "H1wsCJjez", "Bk-6h6Txz", "B1E57a-ZG", "SkESQBOMz", "ryOeXB_Mf", "r1SpfB_fG", "ryKwMH_Mz" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "the paper is clearly written; it works on a popular idea of combining graphical models and neural nets.\n\nthis work could benefit from differentiating more from previous literature.\n\none key component is interpretability, which comes from the use of graphical models. the authors claim that the previous art dir...	[ 6, 6, 6, -1, -1, -1, -1 ]	[ 5, 2, 3, -1, -1, -1, -1 ]	[ "iclr_2018_HJUOHGWRb", "iclr_2018_HJUOHGWRb", "iclr_2018_HJUOHGWRb", "H1wsCJjez", "Bk-6h6Txz", "B1E57a-ZG", "iclr_2018_HJUOHGWRb" ]
iclr_2018_HyPpD0g0Z	Grouping-By-ID: Guarding Against Adversarial Domain Shifts	When training a deep neural network for supervised image classification, one can broadly distinguish between two types of latent features of images that will drive the classification of class Y. Following the notation of Gong et al. (2016), we can divide features broadly into the classes of (i) “core” or “conditionally...	rejected-papers	The paper proposes a method to robustify neural networks which is an important problem. They uses ideas from causality and create a model that would only depend on "stable" features ignoring the easy to manipulate ones. The paper has some interesting ideas, however, the main concern is regarding insufficient comparison...	train	[ "rJqVoyclf", "SkKuc-Kef", "BkDbv9qlM", "HyyaEhBbG", "SJ0jX3Bbz", "rJmAGnrbG", "ryWwGhrWf" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "The paper discusses ways to guard against adversarial domain shifts with so-called counterfactual regularization. The main idea is that in several datasets there are many instances of images for the same object/person, and that taking this into account by learning a classifier that is invariant to the superficial ...	[ 7, 4, 5, -1, -1, -1, -1 ]	[ 3, 5, 4, -1, -1, -1, -1 ]	[ "iclr_2018_HyPpD0g0Z", "iclr_2018_HyPpD0g0Z", "iclr_2018_HyPpD0g0Z", "SkKuc-Kef", "rJqVoyclf", "BkDbv9qlM", "BkDbv9qlM" ]
iclr_2018_H1xJjlbAZ	INTERPRETATION OF NEURAL NETWORK IS FRAGILE	In order for machine learning to be deployed and trusted in many applications, it is crucial to be able to reliably explain why the machine learning algorithm makes certain predictions. For example, if an algorithm classifies a given pathology image to be a malignant tumor, then the doctor may need to know which parts ...	rejected-papers	The paper tries to show that many of the state-of-the-art interpretability methods are brittle and do not provide consistent stable explanations. The authors show this by perturbing (even randomly) the inputs so that the differences are imperceptible to a human observer but the interpretability methods provide complete...	test	[ "HJIRZCbeG", "S1Z4Lgqez", "Sk-uqZ9xG", "rkjVKPJGG", "H1XWYv1GM", "SkDAOvkfz", "HktDzGqgf", "BkgXE1qef", "SJBmRuQxG", "S1UARBXgG", "HkJSs4Xlf", "Sk7hGWhkM", "SJtR6e3kz", "BJhbOjiJG", "HyNgEDoJM", "SylgNFXJf", "ryEWYqGJM", "HJAUq8CA-", "r1g2UGCRZ", "HyA39DpR-" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "public", "public", "author", "public", "author", "public", "author", "public", "public", "author", "public", "author", "public" ]	[ "The authors study cases where interpretation of deep learning predictions is extremely fragile. They systematically characterize the fragility of several widely-used feature-importance interpretation methods. In general, questioning the reliability of the visualization techniques is interesting. Regarding the tech...	[ 6, 4, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 ]	[ 2, 4, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1 ]	[ "iclr_2018_H1xJjlbAZ", "iclr_2018_H1xJjlbAZ", "iclr_2018_H1xJjlbAZ", "HJIRZCbeG", "S1Z4Lgqez", "Sk-uqZ9xG", "BkgXE1qef", "iclr_2018_H1xJjlbAZ", "S1UARBXgG", "HkJSs4Xlf", "iclr_2018_H1xJjlbAZ", "SJtR6e3kz", "BJhbOjiJG", "HyNgEDoJM", "iclr_2018_H1xJjlbAZ", "ryEWYqGJM", "HJAUq8CA-", "...
iclr_2018_S1EzRgb0W	Explaining the Mistakes of Neural Networks with Latent Sympathetic Examples	Neural networks make mistakes. The reason why a mistake is made often remains a mystery. As such neural networks often are considered a black box. It would be useful to have a method that can give an explanation that is intuitive to a user as to why an image is misclassified. In this paper we develop a method for expla...	rejected-papers	The paper proposes a way to find why a classifier misclassified a certain instance. It tries to find pertubations in the input space to identify the appropriate reasons for the misclassification. The reviewers feel that the idea is interesting, however, it is insufficiently evaluated. Even for the datasets they do eva...	train	[ "BJncxx9gf", "HJ3Gw8clz", "B1IHpaWWM", "BkKZxuaQz", "S1an1uaQz", "HyhKJ_pXM", "rJ072Pa7f" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "This paper proposes a method for explaining the classification mistakes of neural networks. For a misclassified image, gradient descent is used to find the minimal change to the input image so that it will be correctly classified. \n\nMy understanding is that the proposed method does not explain why a classifier m...	[ 4, 4, 6, -1, -1, -1, -1 ]	[ 5, 3, 4, -1, -1, -1, -1 ]	[ "iclr_2018_S1EzRgb0W", "iclr_2018_S1EzRgb0W", "iclr_2018_S1EzRgb0W", "BJncxx9gf", "HJ3Gw8clz", "B1IHpaWWM", "iclr_2018_S1EzRgb0W" ]
iclr_2018_r1Oen--RW	The (Un)reliability of saliency methods	Saliency methods aim to explain the predictions of deep neural networks. These methods lack reliability when the explanation is sensitive to factors that do not contribute to the model prediction. We use a simple and common pre-processing step ---adding a mean shift to the input data--- to show that a transformation wi...	rejected-papers	This paper showcases how saliency methods are brittle and cannot be trusted to obtain robust explanations. They define a property called input invariance that they claim all reliable explanation methods must possess. The reviewers have concerns regarding the motivation of this property in terms of why is it needed. Thi...	train	[ "BJ6e_ttgf", "HyVpmntgG", "B1nPks1-f", "BkVa3BTQz", "By_xnrTQf", "S14SnSpmM", "rk1tiS67M" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "The scope of the paper is interesting i.e. taking a closer look at saliency methods in view of explaining deep learning neural networks. The authors state that saliency methods that do not satisfy an input invariance property can be misleading.\n\nOn the other hand the paper can be improved in my opinion in differ...	[ 5, 4, 4, -1, -1, -1, -1 ]	[ 3, 4, 4, -1, -1, -1, -1 ]	[ "iclr_2018_r1Oen--RW", "iclr_2018_r1Oen--RW", "iclr_2018_r1Oen--RW", "BJ6e_ttgf", "B1nPks1-f", "HyVpmntgG", "iclr_2018_r1Oen--RW" ]
iclr_2018_SJPpHzW0-	Influence-Directed Explanations for Deep Convolutional Networks	We study the problem of explaining a rich class of behavioral properties of deep neural networks. Our influence-directed explanations approach this problem by peering inside the network to identify neurons with high influence on the property of interest using an axiomatically justified influence measure, and then provi...	rejected-papers	The paper defines a new measure of influence and uses it to highlight important features. The definition is novel however, the reviewers have concerns regarding its significance, novelty and a thorough empirical comparison to existing literature is missing.	train	[ "ryI_k_PeM", "r1ieZZcxf", "HyPSFK2gf" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "Notions of \"influence\" have become popular recently, and these notions try to understand how the output of a classifier or a learning algorithm is influenced by its training set. In this paper, the authors propose a way to measure influence that satisfies certain axioms. This notion of influence may be used to i...	[ 5, 4, 4 ]	[ 3, 5, 3 ]	[ "iclr_2018_SJPpHzW0-", "iclr_2018_SJPpHzW0-", "iclr_2018_SJPpHzW0-" ]
iclr_2018_rJhR_pxCZ	Interpretable Classification via Supervised Variational Autoencoders and Differentiable Decision Trees	As deep learning-based classifiers are increasingly adopted in real-world applications, the importance of understanding how a particular label is chosen grows. Single decision trees are an example of a simple, interpretable classifier, but are unsuitable for use with complex, high-dimensional data. On the other hand, t...	rejected-papers	The paper proposes a new model called differential decision tree which captures the benefits of decision trees and VAEs. They evaluate the method only on the MNIST dataset. The reviewers thus rightly complain that the evaluation is thus insufficient and one also questions its technical novelty.	train	[ "SJCjWdiJG", "H1v-LprxG", "HktiHfugG", "Sy9KgIP-G", "rJ09X3Tlf" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author" ]	[ "\nSummary\n\nThis paper proposes a hybrid model (C+VAE)---a variational autoencoder (VAE) composed with a differentiable decision tree (DDT)---and an accompanying training scheme. Firstly, the prior is specified as a mixture distribution with one component per class (SVAE). During training, the ELBO’s KL term us...	[ 3, 4, 5, -1, -1 ]	[ 5, 4, 4, -1, -1 ]	[ "iclr_2018_rJhR_pxCZ", "iclr_2018_rJhR_pxCZ", "iclr_2018_rJhR_pxCZ", "iclr_2018_rJhR_pxCZ", "iclr_2018_rJhR_pxCZ" ]
iclr_2018_B1ydPgTpW	Predicting Auction Price of Vehicle License Plate with Deep Recurrent Neural Network	In Chinese societies, superstition is of paramount importance, and vehicle license plates with desirable numbers can fetch very high prices in auctions. Unlike other valuable items, license plates are not allocated an estimated price before auction. I propose that the task of predicting plate prices can b...	rejected-papers	Reviewers concur that the paper and the application area are interesting but that the approaches are not sufficiently novel to justify presentation at ICLR.	val	[ "r1ffKGS4M", "rkMjOyqlM", "BJT4Wx5ez", "Bk3B7T5gf", "ryXwsKp7M", "S1xQ8F67M" ]	[ "author", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author" ]	[ "Thank you for your detailed comments and suggestions. The following are improvements I have made:\n- The odd reference in the introduction was in response to a referee's inquiry in a previous submission. It has been removed. The introduction has also been shortened.\n- Citation has been added for Akita et al.\n- T...	[ -1, 6, 4, 4, -1, -1 ]	[ -1, 5, 4, 4, -1, -1 ]	[ "BJT4Wx5ez", "iclr_2018_B1ydPgTpW", "iclr_2018_B1ydPgTpW", "iclr_2018_B1ydPgTpW", "Bk3B7T5gf", "rkMjOyqlM" ]
iclr_2018_HJcjQTJ0W	PrivyNet: A Flexible Framework for Privacy-Preserving Deep Neural Network Training	Massive data exist among user local platforms that usually cannot support deep neural network (DNN) training due to computation and storage resource constraints. Cloud-based training schemes provide beneficial services but suffer from potential privacy risks due to excessive user data collection. To enable cloud-based ...	rejected-papers	Reviews are marginal. I concur with the two less-favorable reviews that the metrics for privacy protection are not sufficiently strong for preserving privacy.	train	[ "HyAGOnOgM", "ryOaYRdez", "SJKRQb5lz" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "1. This is an interesting paper - introduces useful concepts such as the formulation of the utility and privacy loss functions with respect to the learning paradigm\n2. From the initial part of the paper, it seems that the proposed PrivyNet is supposed to be a meta-learning framework to split a DNN in order to imp...	[ 6, 5, 3 ]	[ 5, 3, 3 ]	[ "iclr_2018_HJcjQTJ0W", "iclr_2018_HJcjQTJ0W", "iclr_2018_HJcjQTJ0W" ]
iclr_2018_H1DJFybC-	Learning to Infer Graphics Programs from Hand-Drawn Images	We introduce a model that learns to convert simple hand drawings into graphics programs written in a subset of \LaTeX.~The model combines techniques from deep learning and program synthesis. We learn a convolutional neural network that proposes plausible drawing primitives that explai...	rejected-papers	The paper addresses an interesting problem, is novel and works. While the paper improved through reviews + rebuttal, the reviewers still find the presentation lacking.	train	[ "ryUoLK6VG", "Sk-ZlwcgG", "B1Te809gM", "HJR0yoJ-z", "B1Rzx_Zzf", "HyOFkdZMG", "ryAfyd-fz" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "I think the paper became better. However, it still needs more work.\n\nOverall, it is not very clear what to be solved in the paper -- if they want to verify the trace hypothesis, or they want to show that the combination of the proposed components is important to build a system for the problem, or the improvement...	[ -1, 4, 6, 4, -1, -1, -1 ]	[ -1, 4, 4, 2, -1, -1, -1 ]	[ "ryAfyd-fz", "iclr_2018_H1DJFybC-", "iclr_2018_H1DJFybC-", "iclr_2018_H1DJFybC-", "Sk-ZlwcgG", "B1Te809gM", "HJR0yoJ-z" ]
iclr_2018_HJWGdbbCW	Reinforcement and Imitation Learning for Diverse Visuomotor Skills	We propose a general deep reinforcement learning method and apply it to robot manipulation tasks. Our approach leverages demonstration data to assist a reinforcement learning agent in learning to solve a wide range of tasks, mainly previously unsolved. We train visuomotor policies end-to-end to learn a direct mapping f...	rejected-papers	While the reviewers agree that this paper does provide a contribution, it is small and does overlap with several concurrent works. it is a bit hand-engineered. The authors have provided a lengthy rebuttal, but the final reviews are not strong enough.	train	[ "rySp4xnBf", "Bkc_ExhHf", "ByNRqb5lz", "B1oZGo_ez", "ry6Xu6UEz", "r1C8JhrNz", "HJge1dvgz", "rJA2tLHQM", "BkVdKIrmf" ]	[ "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author" ]	[ "We thank this reviewer for the additional feedback. We would like to address the reviewer’s comments on the use of simulation and the amount of hand engineering in this work. We will also make an effort to clearly describe our engineering components in the next version of the draft.\n\nWe acknowledged that simulat...	[ -1, -1, 4, 4, -1, -1, 6, -1, -1 ]	[ -1, -1, 4, 4, -1, -1, 5, -1, -1 ]	[ "ry6Xu6UEz", "r1C8JhrNz", "iclr_2018_HJWGdbbCW", "iclr_2018_HJWGdbbCW", "B1oZGo_ez", "HJge1dvgz", "iclr_2018_HJWGdbbCW", "BkVdKIrmf", "iclr_2018_HJWGdbbCW" ]
iclr_2018_S1FFLWWCZ	LSD-Net: Look, Step and Detect for Joint Navigation and Multi-View Recognition with Deep Reinforcement Learning	Multi-view recognition is the task of classifying an object from multi-view image sequences. Instead of using a single-view for classification, humans generally navigate around a target object to learn its multi-view representation. Motivated by this human behavior, the next best view can be learned by combining object...	rejected-papers	This paper describes active vision for object recognition learned in an RL framework. Reviewers think the paper is not of sufficient quality: Insufficient detail, and insufficient evaluation. While the authors have provided a lengthy rebuttal, the shortcomings have not yet been addressed in the paper.	train	[ "rJKiKBGef", "Bk9Z3ZQlG", "HJwAZZvxG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "Paper Summary: The paper proposes an approach to perform object classification and changing the viewpoint simultaneously. The idea is that the viewpoint changes until the object is recognized. The results have been reported on ModelNet40.\n\nPaper Strength: The idea of combining active vision with object classific...	[ 4, 6, 3 ]	[ 4, 4, 4 ]	[ "iclr_2018_S1FFLWWCZ", "iclr_2018_S1FFLWWCZ", "iclr_2018_S1FFLWWCZ" ]
iclr_2018_SkmM6M_pW	Egocentric Spatial Memory Network	Inspired by neurophysiological discoveries of navigation cells in the mammalian brain, we introduce the first deep neural network architecture for modeling Egocentric Spatial Memory (ESM). It learns to estimate the pose of the agent and progressively construct top-down 2D global maps from egocentric v...	rejected-papers	Authors do not respond to significant criticism - e.g. lack of a critical reference Reviewers unanimously reject.	train	[ "r1hg0NjgG", "BkfIZxFlG", "Bk5nrSoeG" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "The paper is well written, well-motivated and the idea is very interesting for the computer vision and robotic communities. The technical contribution is original. The vision-based agent localization approach is novel compared to the methods of the literature. However, the experimental validation of the proposed a...	[ 5, 3, 4 ]	[ 4, 4, 4 ]	[ "iclr_2018_SkmM6M_pW", "iclr_2018_SkmM6M_pW", "iclr_2018_SkmM6M_pW" ]
iclr_2018_rJqfKPJ0Z	Clipping Free Attacks Against Neural Networks	During the last years, a remarkable breakthrough has been made in AI domain thanks to artificial deep neural networks that achieved a great success in many machine learning tasks in computer vision, natural language processing, speech recognition, malware detection and so on. However, they are highly ...	rejected-papers	The reviewers have various reservations. While the paper has interesting suggestions, it is slightly incremental and the results are not sufficiently compared to other techniques. We not that one reviewer revised his opinion	train	[ "B1fZIQcxM", "ryU7ZMsgf", "BkrIo4ixG", "ryWp9xwGf", "SkWHqxDzf", "Byu9txvMM" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "The paper is not anonymized. In page 2, the first line, the authors revealed [15] is a self-citation and [15] is not anonumized in the reference list.\n\n", "This paper presents a reparametrization of the perturbation applied to features in adversarial examples based attacks. It tests this attack variation on ag...	[ 3, 4, 5, -1, -1, -1 ]	[ 3, 3, 2, -1, -1, -1 ]	[ "iclr_2018_rJqfKPJ0Z", "iclr_2018_rJqfKPJ0Z", "iclr_2018_rJqfKPJ0Z", "B1fZIQcxM", "ryU7ZMsgf", "BkrIo4ixG" ]
iclr_2018_ByCPHrgCW	Deep Learning Inferences with Hybrid Homomorphic Encryption	When deep learning is applied to sensitive data sets, many privacy-related implementation issues arise. These issues are especially evident in the healthcare, finance, law and government industries. Homomorphic encryption could allow a server to make inferences on inputs encrypted by a client, but to our best knowledge...	rejected-papers	While the reviewers all seem to think this is interesting and basically good work, the Reviewers are consistent and unanimous in rejecting the paper. While the authors did provide a thorough rebuttal, the original paper did not meet the criteria and the reviewers have not changed their scores.	train	[ "HkCG-X5lG", "rJhC64Olf", "Sy52MUdgG", "S174cGs7z", "BJxS1hFXG", "ryMApotmG", "B1p3soF7z" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author" ]	[ "This paper proposes a hybrid Homomorphic encryption system that is well suited for privacy-sensitive data inference applications with the deep learning paradigm. \nThe paper presents a well laid research methodology that shows a good decomposition of the problem at hand and the approach foreseen to solve it. It is...	[ 4, 4, 4, -1, -1, -1, -1 ]	[ 4, 5, 5, -1, -1, -1, -1 ]	[ "iclr_2018_ByCPHrgCW", "iclr_2018_ByCPHrgCW", "iclr_2018_ByCPHrgCW", "iclr_2018_ByCPHrgCW", "rJhC64Olf", "Sy52MUdgG", "HkCG-X5lG" ]
iclr_2018_H1u8fMW0b	Toward predictive machine learning for active vision	We develop a comprehensive description of the active inference framework, as proposed by Friston (2010), under a machine-learning compliant perspective. Stemming from a biological inspiration and the auto-encoding principles, a sketch of a cognitive architecture is proposed that should provide ways to implement estimat...	rejected-papers	All 3 reviewers consider the paper insufficiently good, including a post-rebuttal updated score. All reviewers + anonymous comment find that the paper isn't well-enough situated with the appropriate literature. Two reviewers cite poor presentation - spelling /grammar errors making hte paper hard to read. Authors have r...	train	[ "SyKJh-qlM", "Hy9KrjINf", "HJedzYOxf", "HkEi3Koxf", "BJLFk84-G", "rJenZIEbf", "Bk9Se8NZM" ]	[ "official_reviewer", "author", "official_reviewer", "official_reviewer", "author", "author", "author" ]	[ "This paper introduces a machine learning adaptation of the active inference framework proposed by Friston (2010), and applies it to the task of image classification on MNIST through a foveated inspection of images. It describes a cognitive architecture for the same, and provide analyses in terms of processing comp...	[ 5, -1, 3, 3, -1, -1, -1 ]	[ 2, -1, 4, 5, -1, -1, -1 ]	[ "iclr_2018_H1u8fMW0b", "HJedzYOxf", "iclr_2018_H1u8fMW0b", "iclr_2018_H1u8fMW0b", "HkEi3Koxf", "HJedzYOxf", "SyKJh-qlM" ]
iclr_2018_r1ayG7WRZ	Don't encrypt the data; just approximate the model \ Towards Secure Transaction and Fair Pricing of Training Data	As machine learning becomes ubiquitous, deployed systems need to be as accu- rate as they can. As a result, machine learning service providers have a surging need for useful, additional training data that benefits training, without giving up all the details about the trained program. At the same time, data owners would...	rejected-papers	The reviewers highlight a lack of technical content and poor writing. They all agree on rejection. There was no author rebuttal or pointer to a new version.	test	[ "Hy0ZkHuxG", "BktJHw_lM", "BJ8Ijatxz" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "Summary\n\nThe paper addresses the issues of fair pricing and secure transactions between model and data providers in the context of machine learning real-world application.\n\nMajor\n\nThe paper addresses an important issue regarding the real-world application of machine learning, that is, the transactions betwee...	[ 2, 4, 3 ]	[ 4, 5, 5 ]	[ "iclr_2018_r1ayG7WRZ", "iclr_2018_r1ayG7WRZ", "iclr_2018_r1ayG7WRZ" ]
iclr_2018_H1BHbmWCZ	TOWARDS ROBOT VISION MODULE DEVELOPMENT WITH EXPERIENTIAL ROBOT LEARNING	n this paper we present a thrust in three directions of visual development us- ing supervised and semi-supervised techniques. The first is an implementation of semi-supervised object detection and recognition using the principles of Soft At- tention and Generative Adversarial Networks (GANs). The second and the third a...	rejected-papers	Reviewers unanimous on rejection. Authors don't maintain anonymity. No rebuttal from authors. Poorly written	train	[ "S1w1mX_xG", "B1IfKjYgM", "B1XsJ_3lf" ]	[ "official_reviewer", "official_reviewer", "official_reviewer" ]	[ "The paper is motivated with building robots that learn in an open-ended way, which is really interesting. What it actually investigates is the performance of existing image classifiers and object detectors. I could not find any technical contribution or something sufficiently mature and interesting for presenting ...	[ 3, 2, 2 ]	[ 4, 3, 4 ]	[ "iclr_2018_H1BHbmWCZ", "iclr_2018_H1BHbmWCZ", "iclr_2018_H1BHbmWCZ" ]

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