input stringlengths 331 3.18k | output list |
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### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Generative Adversarial Networks (GANs) have proven to be a powerful framework for learning to draw samples from complex distributions.', 'However, GANs are also notoriously difficult to train, with mode colla... | [
"Generative Adversarial Network Training is a Continual Learning Problem."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Many problems with large-scale labeled training data have been impressively solved by deep learning.', 'However, Unseen Class Categorization (UCC) with minimal information provided about target classes is the... | [
"A unified frame for both few-shot learning and zero-shot learning based on network reparameterization"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Proteins are ubiquitous molecules whose function in biological processes is determined by their 3D structure.\n', "Experimental identification of a protein's structure can be time-consuming, prohibitively exp... | [
"GraphQA is a graph-based method for protein Quality Assessment that improves the state-of-the-art for both hand-engineered and representation-learning approaches"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['We study the problem of training machine learning models incrementally using active learning with access to imperfect or noisy oracles.', 'We specifically consider the setting of batch active learning, in whi... | [
"We address the active learning in batch setting with noisy oracles and use model uncertainty to encode the decision quality of active learning algorithm during acquisition."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Artistic style transfer is the problem of synthesizing an image with content similar to a given image and style similar to another.', "Although recent feed-forward neural networks can generate stylized images... | [
"Stochastic style transfer with adjustable features. "
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Recent work has shown that deep reinforcement-learning agents can learn to follow language-like instructions from infrequent environment rewards.', 'However, this places on environment designers the onus of d... | [
"We propose AGILE, a framework for training agents to perform instructions from examples of respective goal-states."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['We present Multitask Soft Option Learning (MSOL), a hierarchical multi-task framework based on Planning-as-Inference.', 'MSOL extends the concept of Options, using separate variational posteriors for each tas... | [
"In Hierarchical RL, we introduce the notion of a 'soft', i.e. adaptable, option and show that this helps learning in multitask settings."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['We propose an algorithm, guided variational autoencoder (Guided-VAE), that is able to learn a controllable generative model by performing latent representation disentanglement learning.', 'The learning object... | [
"Learning a controllable generative model by performing latent representation disentanglement learning."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Neural language models (NLMs) are generative, and they model the distribution of grammatical sentences.', 'Trained on huge corpus, NLMs are pushing the limit of modeling accuracy.', 'Besides, they have also b... | [
"Enhance the language model for supervised learning task "
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Conventionally, convolutional neural networks (CNNs) process different images with the same set of filters.', 'However, the variations in images pose a challenge to this fashion.', 'In this paper, we propose ... | [
"dynamically generate filters conditioned on the input image for CNNs in each forward pass "
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['We propose a new anytime neural network which allows partial evaluation by subnetworks with different widths as well as depths.', 'Compared to conventional anytime networks only with the depth controllability... | [
"We propose a new anytime neural network which allows partial evaluation by subnetworks with different widths as well as depths."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['We propose a new model for making generalizable and diverse retrosynthetic reaction predictions.', 'Given a target compound, the task is to predict the likely chemical reactants to produce the target.', 'This... | [
"We propose a new model for making generalizable and diverse retrosynthetic reaction predictions."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Unsupervised learning of disentangled representations is an open problem in machine learning.', 'The Disentanglement-PyTorch library is developed to facilitate research, implementation, and testing of new var... | [
"Disentanglement-PyTorch is a library for variational representation learning"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Trust region methods, such as TRPO, are often used to stabilize policy optimization algorithms in reinforcement learning (RL).', 'While current trust region strategies are effective for continuous control, th... | [
"We extend recent insights related to softmax consistency to achieve state-of-the-art results in continuous control."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Deep reinforcement learning has achieved many recent successes, but our understanding of its strengths and limitations is hampered by the lack of rich environments in which we can fully characterize optimal b... | [
"We adapt a family of combinatorial games with tunable difficulty and an optimal policy expressible as linear network, developing it as a rich environment for reinforcement learning, showing contrasts in performance with supervised learning, and analyzing multiagent learning and generalization. "
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Adoption of deep learning in safety-critical systems raise the need for understanding what deep neural networks do not understand.', 'Several methodologies to estimate model uncertainty have been proposed, bu... | [
"An add-on method for deep learning to detect outliers during prediction-time"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['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.', '... | [
"A fully connected architecture is used to produce word embeddings from character representations, outperforms traditional embeddings and provides insight into sparsity and dropout."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Neural networks with low-precision weights and activations offer compelling\n', 'efficiency advantages over their full-precision equivalents.', 'The two most\n', 'frequently discussed benefits of quantization... | [
"We conduct adversarial attacks against binarized neural networks and show that we reduce the impact of the strongest attacks, while maintaining comparable accuracy in a black-box setting"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Unsupervised bilingual dictionary induction (UBDI) is useful for unsupervised machine translation and for cross-lingual transfer of models into low-resource languages.', 'One approach to UBDI is to align word... | [
"An empirical investigation of GAN-based alignment of word vector spaces, focusing on cases, where linear transformations provably exist, but training is unstable."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Owing to the ubiquity of computer software, software vulnerability detection (SVD) has become an important problem in the software industry and in the field of computer security.', 'One of the most crucial is... | [
"Our aim in this paper is to propose a new approach for tackling the problem of transfer learning from labeled to unlabeled software projects in the context of SVD in order to resolve the mode collapsing problem faced in previous approaches."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Representation learning is one of the foundations of Deep Learning and allowed important improvements on several Machine Learning tasks, such as Neural Machine Translation, Question Answering and Speech Recog... | [
"A faster method for generating node embeddings that employs a number of permutations over a node's immediate neighborhood as context to generate its representation."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Orthogonal recurrent neural networks address the vanishing gradient problem by parameterizing the recurrent connections using an orthogonal matrix.', 'This class of models is particularly effective to solve t... | [
"We show how to initialize recurrent architectures with the closed-form solution of a linear autoencoder for sequences. We show the advantages of this approach compared to orthogonal RNNs."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['This paper improves upon the line of research that formulates named entity recognition (NER) as a sequence-labeling problem.', 'We use so-called black-box long short-term memory (LSTM) encoders to achieve sta... | [
"We provide insightful understanding of sequence-labeling NER and propose to use two types of cross structures, both of which bring theoretical and empirical improvements."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Knowledge Graph Embedding (KGE) is the task of jointly learning entity and relation embeddings for a given knowledge graph.', 'Existing methods for learning KGEs can be seen as a two-stage process where', '(a... | [
"We present a theoretically proven generative model of knowledge graph embedding. "
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Currently the only techniques for sharing governance of a deep learning model are homomorphic encryption and secure multiparty computation.', 'Unfortunately, neither of these techniques is applicable to the t... | [
"We study empirically how hard it is to recover missing parts of trained models"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['This paper proposes variational domain adaptation, a unified, scalable, simple framework for learning multiple distributions through variational inference.', 'Unlike the existing methods on domain transfer th... | [
"This paper proposes variational domain adaptation, a unified, scalable, simple framework for learning multiple distributions through variational inference"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['We propose a new method to train neural networks based on a novel combination of adversarial training and provable defenses.', 'The key idea is to model training as a procedure which includes both, the verifi... | [
"We propose a novel combination of adversarial training and provable defenses which produces a model with state-of-the-art accuracy and certified robustness on CIFAR-10. "
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
["Learning tasks on source code (i.e., formal languages) have been considered recently, but most work has tried to transfer natural language methods and does not capitalize on the unique opportunities offered b... | [
"Programs have structure that can be represented as graphs, and graph neural networks can learn to find bugs on such graphs"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Overfitting is an ubiquitous problem in neural network training and usually mitigated using a holdout data set.\n', 'Here we challenge this rationale and investigate criteria for overfitting without using a h... | [
"We introduce and analyze several criteria for detecting overfitting."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Partially observable Markov decision processes (POMDPs) are a widely-used framework to model decision-making with uncertainty about the environment and under stochastic outcome.', 'In conventional POMDP model... | [
"We develop a point-based value iteration solver for POMDPs with active perception and planning tasks."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Deep neural networks, in particular convolutional neural networks, have become highly effective tools for compressing images and solving inverse problems including denoising, inpainting, and reconstruction fr... | [
"We introduce an underparameterized, nonconvolutional, and simple deep neural network that can, without training, effectively represent natural images and solve image processing tasks like compression and denoising competitively."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['In this paper we investigate the family of functions representable by deep neural networks (DNN) with rectified linear units (ReLU).', 'We give an algorithm to train a ReLU DNN with one hidden layer to {\\em ... | [
"This paper 1) characterizes functions representable by ReLU DNNs, 2) formally studies the benefit of depth in such architectures, 3) gives an algorithm to implement empirical risk minimization to global optimality for two layer ReLU nets."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['The backpropagation of error algorithm (BP) is often said to be impossible to implement in a real brain.', 'The recent success of deep networks in machine learning and AI, however, has inspired a number of pr... | [
"Benchmarks for biologically plausible learning algorithms on complex datasets and architectures"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Deep neural networks (DNNs) usually contain millions, maybe billions, of parameters/weights, making both storage and computation very expensive.', 'This has motivated a large body of work to reduce the comple... | [
"We have proposed using the recent GrOWL regularizer for simultaneous parameter sparsity and tying in DNN learning. "
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Weight-sharing—the simultaneous optimization of multiple neural networks using the same parameters—has emerged as a key component of state-of-the-art neural architecture search.', 'However, its success is poo... | [
"An analysis of the learning and optimization structures of architecture search in neural networks and beyond."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Deep latent variable models have seen recent success in many data domains.', 'Lossless compression is an application of these models which, despite having the potential to be highly useful, has yet to be impl... | [
"We do lossless compression of large image datasets using a VAE, beat existing compression algorithms."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Hyperparameter tuning is arguably the most important ingredient for obtaining state of art performance in deep networks. ', 'We focus on hyperparameters that are related to the optimization algorithm, e.g. ... | [
"Bayesian optimization based online hyperparameter optimization."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Multi-hop text-based question-answering is a current challenge in machine comprehension. \n', 'This task requires to sequentially integrate facts from multiple passages to answer complex natural language ques... | [
"In this paper, we propose the Latent Question Reformulation Network (LQR-net), a multi-hop and parallel attentive network designed for question-answering tasks that require reasoning capabilities."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['We propose a method to automatically compute the importance of features at every observation in time series, by simulating counterfactual trajectories given previous observations.', 'We define the importance ... | [
"Explaining Multivariate Time Series Models by finding important observations in time using Counterfactuals"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['This paper addresses unsupervised domain adaptation, the setting where labeled training data is available on a source domain, but the goal is to have good performance on a target domain with only unlabeled da... | [
"We use self-supervision on both domain to align them for unsupervised domain adaptation."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['We introduce simple, efficient algorithms for computing a MinHash of a probability distribution, suitable for both sparse and dense data, with equivalent running times to the state of the art for both cases.'... | [
"The minimum of a set of exponentially distributed hashes has a very useful collision probability that generalizes the Jaccard Index to probability distributions."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Recently, progress has been made towards improving relational reasoning in machine learning field.', 'Among existing models, graph neural networks (GNNs) is one of the most effective approaches for multi-hop ... | [
"A graph neural network model with parameters generated from natural languages, which can perform multi-hop reasoning. "
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Off-Policy Actor-Critic (Off-PAC) methods have proven successful in a variety of continuous control tasks.', 'Normally, the critic’s action-value function is updated using temporal-difference, and the critic ... | [
"We present Meta-Critic, an auxiliary critic module for off-policy actor-critic methods that can be meta-learned online during single task learning."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Modern neural networks are highly overparameterized, with capacity to substantially overfit to training data.', 'Nevertheless, these networks often generalize well in practice.', 'It has also been observed th... | [
"We obtain non-vacuous generalization bounds on ImageNet-scale deep neural networks by combining an original PAC-Bayes bound and an off-the-shelf neural network compression method."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Adversarial examples can be defined as inputs to a model which induce a mistake -- where the model output is different than that of an oracle, perhaps in surprising or malicious ways.', 'Original models of ad... | [
"We propose an alternative measure for determining effectiveness of adversarial attacks in NLP models according to a distance measure-based method like incremental L2-gain in control theory."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['We propose a Warped Residual Network (WarpNet) using a parallelizable warp operator for forward and backward propagation to distant layers that trains faster than the original residual neural network.', 'We a... | [
"We propose the Warped Residual Network using a parallelizable warp operator for forward and backward propagation to distant layers that trains faster than the original residual neural network. "
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['A plethora of methods attempting to explain predictions of black-box models have been proposed by the Explainable Artificial Intelligence (XAI) community.', 'Yet, measuring the quality of the generated explan... | [
"We propose a suite of metrics that capture desired properties of explainability algorithms and use it to objectively compare and evaluate such methods"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Neural networks are known to produce unexpected results on inputs that are far from the training distribution.', 'One approach to tackle this problem is to detect the samples on which the trained network can ... | [
"A recent out-of-distribution detection method helps to measure the confidence of RNN predictions for some NLP tasks"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Some recent work has shown separation between the expressive power of depth-2 and depth-3 neural networks.', 'These separation results are shown by constructing functions and input distributions, so that the ... | [
"depth-2-vs-3 separation for sigmoidal neural networks over general distributions"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['The smallest eigenvectors of the graph Laplacian are well-known to provide a succinct representation of the geometry of a weighted graph.', 'In reinforcement learning (RL), where the weighted graph may be int... | [
"We propose a scalable method to approximate the eigenvectors of the Laplacian in the reinforcement learning context and we show that the learned representations can improve the performance of an RL agent."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Our work offers a new method for domain translation from semantic label maps\n', 'and Computer Graphic (CG) simulation edge map images to photo-realistic im-\n', 'ages.', 'We train a Generative Adversarial Ne... | [
"Simulation to real images translation and video generation"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Deep neural networks are widely used in various domains, but the prohibitive computational complexity prevents their deployment on mobile devices.', 'Numerous model compression algorithms have been proposed, ... | [
"We propose PocketFlow, an automated framework for model compression and acceleration, to facilitate deep learning models' deployment on mobile devices."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Generative models provide a way to model structure in complex distributions and have been shown to be useful for many tasks of practical interest.', 'However, current techniques for training generative models... | [
"How to learn GANs from noisy, distorted, partial observations"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Random Matrix Theory (RMT) is applied to analyze the weight matrices of Deep Neural Networks (DNNs), including both production quality, pre-trained models such as AlexNet and Inception, and smaller models tra... | [
"See the abstract. (For the revision, the paper is identical, except for a 59 page Supplementary Material, which can serve as a stand-along technical report version of the paper.)"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['We introduce an attention mechanism to improve feature extraction for deep active learning (AL) in the semi-supervised setting.', 'The proposed attention mechanism is based on recent methods to visually expla... | [
"We introduce an attention mechanism to improve feature extraction for deep active learning (AL) in the semi-supervised setting."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['We apply canonical forms of gradient complexes (barcodes) to explore neural networks loss surfaces.', "We present an algorithm for calculations of the objective function's barcodes of minima. ", "Our experim... | [
"We apply canonical forms of gradient complexes (barcodes) to explore neural networks loss surfaces."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['\nNew 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 ... | [
"Using asynchronous gradient updates to accelerate dynamic neural network training"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['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... | [
"We study reward design problem in cooperative MARL based on packet routing environments. The experimental results remind us to be careful to design the rewards, as they are really important to guide the agent behavior."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Recent advances have illustrated that it is often possible to learn to solve linear inverse problems in imaging using training data that can outperform more traditional regularized least squares solutions.', ... | [
"Neumann networks are an end-to-end, sample-efficient learning approach to solving linear inverse problems in imaging that are compatible with the MSE optimal approach and admit an extension to patch-based learning."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['End-to-end task-oriented dialogue is challenging since knowledge bases are usually large, dynamic and hard to incorporate into a learning framework.', 'We propose the global-to-local memory pointer (GLMP) net... | [
"GLMP: Global memory encoder (context RNN, global pointer) and local memory decoder (sketch RNN, local pointer) that share external knowledge (MemNN) are proposed to strengthen response generation in task-oriented dialogue."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['The checkerboard phenomenon is one of the well-known visual artifacts in the computer vision field.', 'The origins and solutions of checkerboard artifacts in the pixel space have been studied for a long time,... | [
"We propose a novel aritificial checkerboard enhancer (ACE) module which guides attacks to a pre-specified pixel space and successfully defends it with a simple padding operation."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Min-max formulations have attracted great attention in the ML community due to the rise of deep generative models and adversarial methods, and understanding the dynamics of (stochastic) gradient algorithms fo... | [
"We systematically analyze the convergence behaviour of popular gradient algorithms for solving bilinear games, with both simultaneous and alternating updates."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Most approaches in generalized zero-shot learning rely on cross-modal mapping between an image feature space and a class embedding space or on generating artificial image features.', 'However, learning a shar... | [
"We use VAEs to learn a shared latent space embedding between image features and attributes and thereby achieve state-of-the-art results in generalized zero-shot learning."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Intuitively, image classification should profit from using spatial information.', 'Recent work, however, suggests that this might be overrated in standard CNNs.', 'In this paper, we are pushing the envelope a... | [
"Spatial information at last layers is not necessary for a good classification accuracy."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Disentangling underlying generative factors of a data distribution is important for interpretability and generalizable representations.', 'In this paper, we introduce two novel disentangling methods.', 'Our ... | [
"We use Siamese Networks to guide and disentangle the generation process in GANs without labeled data."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['We present Predicted Variables, an approach to making machine learning (ML) a first class citizen in programming languages.\n', 'There is a growing divide in approaches to building systems: using human expert... | [
"We present Predicted Variables, an approach to making machine learning a first class citizen in programming languages."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Much recent research has been devoted to video prediction and generation, but mostly for short-scale time horizons.', 'The hierarchical video prediction method by Villegas et al. (2017) is an example of a st... | [
"We show ways to train a hierarchical video prediction model without needing pose labels."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Combining information from different sensory modalities to execute goal directed actions is a key aspect of human intelligence.', 'Specifically, human agents are very easily able to translate the task communi... | [
"In this work, we study the problem of learning representations to identify novel objects by exploring objects using tactile sensing. Key point here is that the query is provided in image domain."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Locality sensitive hashing schemes such as \\simhash provide compact representations of multisets from which similarity can be estimated.', 'However, in certain applications, we need to estimate the similarit... | [
"We employ linear homomorphic compression schemes to represent the sufficient statistics of a conditional random field model of coreference and this allows us to scale inference and improve speed by an order of magnitude."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Motivated by applications to unsupervised learning, we consider the problem of measuring mutual information.', 'Recent analysis has shown that naive kNN estimators of mutual information have serious statistic... | [
"We give a theoretical analysis of the measurement and optimization of mutual information."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['In this paper, we propose a neural network framework called neuron hierarchical network (NHN), that evolves beyond the hierarchy in layers, and concentrates on the hierarchy of neurons.', 'We observe mass red... | [
"By breaking the layer hierarchy, we propose a 3-step approach to the construction of neuron-hierarchy networks that outperform NAS, SMASH and hierarchical representation with fewer parameters and shorter searching time."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Simulation is a useful tool in situations where training data for machine learning models is costly to annotate or even hard to acquire.', 'In this work, we propose a reinforcement learning-based method for a... | [
"We propose an algorithm that automatically adjusts parameters of a simulation engine to generate training data for a neural network such that validation accuracy is maximized."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Modelling statistical relationships beyond the conditional mean is crucial in many settings.', 'Conditional density estimation (CDE) aims to learn the full conditional probability density from data.', 'Though... | [
"A model-agnostic regularization scheme for neural network-based conditional density estimation."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Unsupervised representation learning holds the promise of exploiting large amount of available unlabeled data to learn general representations.', 'A promising technique for unsupervised learning is the framew... | [
"A patch-based bottleneck formulation in a VAE framework that learns unsupervised representations better suited for visual recognition."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Vanishing and exploding gradients are two of the main obstacles in training deep neural networks, especially in capturing long range dependencies in recurrent neural networks (RNNs).', 'In this paper, we pres... | [
"To solve the gradient vanishing/exploding problems, we proprose an efficient parametrization of the transition matrix of RNN that loses no expressive power, converges faster and has good generalization."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Recent image style transferring methods achieved arbitrary stylization with input content and style images.', 'To transfer the style of an arbitrary image to a content image, these methods used a feed-forward... | [
"A paper suggesting a method to transform the style of images using deep neural networks."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Beyond understanding what is being discussed, human communication requires an awareness of what someone is feeling.', 'One challenge for dialogue agents is recognizing feelings in the conversation partner and... | [
"We improve existing dialogue systems for responding to people sharing personal stories, incorporating emotion prediction representations and also release a new benchmark and dataset of empathetic dialogues."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Granger causality is a widely-used criterion for analyzing interactions in large-scale networks.', 'As most physical interactions are inherently nonlinear, we consider the problem of inferring the existence o... | [
"A new recurrent neural network architecture for detecting pairwise Granger causality between nonlinearly interacting time series. "
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Graph convolutional networks (GCNs) are powerful deep neural networks for graph-structured data.', "However, GCN computes nodes' representation recursively from their neighbors, making the receptive field siz... | [
"A control variate based stochastic training algorithm for graph convolutional networks that the receptive field can be only two neighbors per node."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Low bit-width integer weights and activations are very important for efficient inference, especially with respect to lower power consumption.', 'We propose to apply Monte Carlo methods and importance sampling... | [
"Monte Carlo methods for quantizing pre-trained models without any additional training."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['We propose the Information Maximization Autoencoder (IMAE), an information theoretic approach to simultaneously learn continuous and discrete representations in an unsupervised setting.', 'Unlike the Variatio... | [
"Information theoretical approach for unsupervised learning of unsupervised learning of a hybrid of discrete and continuous representations, "
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Learning rules for neural networks necessarily include some form of regularization.', 'Most regularization techniques are conceptualized and implemented in the space of parameters.', 'However, it is also poss... | [
"It's important to consider optimization in function space, not just parameter space. We introduce a learning rule that reduces distance traveled in function space, just like SGD limits distance traveled in parameter space."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Stochastic gradient descent (SGD), which dates back to the 1950s, is one of the most popular and effective approaches for performing stochastic optimization.', 'Research on SGD resurged recently in machine le... | [
"Convergence theory for biased (but consistent) gradient estimators in stochastic optimization and application to graph convolutional networks"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['We consider the problem of uncertainty estimation in the context of (non-Bayesian) deep neural classification.', 'In this context, all known methods are based on extracting uncertainty signals from a trained ... | [
"We use snapshots from the training process to improve any uncertainty estimation method of a DNN classifier."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Existing public face image datasets are strongly biased toward Caucasian faces, and other races (e.g., Latino) are significantly underrepresented.', 'The models trained from such datasets suffer from inconsis... | [
"A new face image dataset for balanced race, gender, and age which can be used for bias measurement and mitigation"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Dramatic advances in generative models have resulted in near photographic quality for artificially rendered faces, animals and other objects in the natural world.', 'In spite of such advances, a higher level ... | [
"We attempt to model the drawing process of fonts by building sequential generative models of vector graphics (SVGs), a highly structured representation of font characters."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['What can we learn about the functional organization of cortical microcircuits from large-scale recordings of neural activity? ', "To obtain an explicit and interpretable model of time-dependent functional co... | [
"We develop 'dynamic neural relational inference', a variational autoencoder model that can explicitly and interpretably represent the hidden dynamic relations between neurons."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['DeePa is a deep learning framework that explores parallelism in all parallelizable dimensions to accelerate the training process of convolutional neural networks.', 'DeePa optimizes parallelism at the granula... | [
"To the best of our knowledge, DeePa is the first deep learning framework that controls and optimizes the parallelism of CNNs in all parallelizable dimensions at the granularity of each layer."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['One can substitute each neuron in any neural network with a kernel machine and obtain a counterpart powered by kernel machines.', 'The new network inherits the expressive power and architecture of the origina... | [
"We combine kernel method with connectionist models and show that the resulting deep architectures can be trained layer-wise and have more transparent learning dynamics. "
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Many notions of fairness may be expressed as linear constraints, and the resulting constrained objective is often optimized by transforming the problem into its Lagrangian dual with additive linear penalties.... | [
"We propose a method to stochastically optimize second-order penalties and show how this may apply to training fairness-aware classifiers."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Training methods for deep networks are primarily variants on stochastic gradient descent. ', 'Techniques that use (approximate) second-order information are rarely used because of the computational cost and ... | [
"We show that deep learning network derivatives have a low-rank structure, and this structure allows us to use second-order derivative information to calculate learning rates adaptively and in a computationally feasible manner."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['The worst-case training principle that minimizes the maximal adversarial loss, also known as adversarial training (AT), has shown to be a state-of-the-art approach for enhancing adversarial robustness against... | [
"A unified min-max optimization framework for adversarial attack and defense"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Most deep learning models rely on expressive high-dimensional representations to achieve good performance on tasks such as classification.', 'However, the high dimensionality of these representations makes th... | [
"dimensionality reduction for cases where examples can be represented as soft probability distributions"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Intrinsically motivated goal exploration algorithms enable machines to discover repertoires of policies that produce a diversity of effects in complex environments.', 'These exploration algorithms have been s... | [
"We propose a novel Intrinsically Motivated Goal Exploration architecture with unsupervised learning of goal space representations, and evaluate how various implementations enable the discovery of a diversity of policies."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['One of the main challenges of deep learning methods is the choice of an appropriate training strategy.', 'In particular, additional steps, such as unsupervised pre-training, have been shown to greatly improve... | [
"We propose an additional training step, called post-training, which computes optimal weights for the last layer of the network."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Natural language processing (NLP) models often require a massive number of parameters for word embeddings, resulting in a large storage or memory footprint.', 'Deploying neural NLP models to mobile devices re... | [
"Compressing the word embeddings over 94% without hurting the performance."
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['It is important to detect anomalous inputs when deploying machine learning systems.', 'The use of larger and more complex inputs in deep learning magnifies the difficulty of distinguishing between anomalous a... | [
"OE teaches anomaly detectors to learn heuristics for detecting unseen anomalies; experiments are in classification, density estimation, and calibration in NLP and vision settings; we do not tune on test distribution samples, unlike previous work"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['While generative neural networks can learn to transform a specific input dataset into a specific target dataset, they require having just such a paired set of input/output datasets.', 'For instance, to fool t... | [
"A method for learning a transformation between one pair of source/target datasets and applying it a separate source dataset for which there is no target dataset"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['In this paper, we propose to combine imitation and reinforcement learning via the idea of reward shaping using an oracle.', 'We study the effectiveness of the near- optimal cost-to-go oracle on the planning h... | [
"Combining Imitation Learning and Reinforcement Learning to learn to outperform the expert"
] |
### Instruction->PROVIDE ME WITH SUMMARY FOR THE GIVEN INPUT WHILE KEEPING THE MOST IMPORTANT DETAILS INTACT:
['Recently, Generative Adversarial Networks (GANs) have emerged as a popular alternative for modeling complex high dimensional distributions.', 'Most of the existing works implicitly assume that the clean sampl... | [
"An unsupervised learning approach for separating two structured signals from their superposition"
] |
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