paper_id large_stringlengths 9 12 | review_id large_stringlengths 9 12 | year int64 2.02k 2.03k | paper_title large_stringlengths 6 202 | paper_abstract large_stringlengths 306 4.31k | system_prompt large_stringclasses 5
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zzk231Ms1Ih | TvyIJI1TlM- | 2,022 | A Theory of Tournament Representations | Real-world tournaments are almost always intransitive. Recent works have noted that parametric models which assume $d$ dimensional node representations can effectively model intransitive tournaments. However, nothing is known about the structure of the class of tournaments that arise out of any fixed $d$ dimensional r... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper studies the theory of tournament representations, i.e. low-rank matrices $M$ whose sign agrees with the sign matrix of a tournament $T$.\n\nThe authors show several properties of such representations, reducing the study to so called $R$-cones, i.e. tournaments where one vertex beats... |
zzk231Ms1Ih | mvJh08SL8ke | 2,022 | A Theory of Tournament Representations | Real-world tournaments are almost always intransitive. Recent works have noted that parametric models which assume $d$ dimensional node representations can effectively model intransitive tournaments. However, nothing is known about the structure of the class of tournaments that arise out of any fixed $d$ dimensional r... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper provides fundamental theories of tournament representations. The authors study two main questions. First they characterize the class of tournaments that can be represented in d dimensions. Second they give lower and upper bounds on the minimum dimension needed to represent a tournam... |
zzk231Ms1Ih | C9NhLV0gKlP | 2,022 | A Theory of Tournament Representations | Real-world tournaments are almost always intransitive. Recent works have noted that parametric models which assume $d$ dimensional node representations can effectively model intransitive tournaments. However, nothing is known about the structure of the class of tournaments that arise out of any fixed $d$ dimensional r... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper studies the relationship between dimensional representation of tournament and their structural characterization. In particular, a relationship is established between rank d tournament and their forbidden configurations in terms of flip classes, introduced by Fisher&Ryan(1995) as a wa... |
zzk231Ms1Ih | pUE59TP-ax | 2,022 | A Theory of Tournament Representations | Real-world tournaments are almost always intransitive. Recent works have noted that parametric models which assume $d$ dimensional node representations can effectively model intransitive tournaments. However, nothing is known about the structure of the class of tournaments that arise out of any fixed $d$ dimensional r... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "A tournament is made by choosing a direction for each of the edges in a complete graph. A tournament can be induced of by skew symmetric matrices M where entries M_{ij} > 0 if and only if (i,j) is an edge. A tournament on n edges can be represented by a set of d-dimensional vectores {h_1, … , ... |
zz9hXVhf40 | KkJogqpzEwc | 2,022 | Revisiting Design Choices in Offline Model Based Reinforcement Learning | Offline reinforcement learning enables agents to leverage large pre-collected datasets of environment transitions to learn control policies, circumventing the need for potentially expensive or unsafe online data collection. Significant progress has been made recently in offline model-based reinforcement learning, appro... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "Recent successful model-based offline RL techniques have relied on heuristics to penalize rewards according to the uncertainty of the estimated MDP. This paper reviews the different penalties that have been designed in the literature. The impact and importance of associated hyperparameters suc... |
zz9hXVhf40 | yfOp35kKfgD | 2,022 | Revisiting Design Choices in Offline Model Based Reinforcement Learning | Offline reinforcement learning enables agents to leverage large pre-collected datasets of environment transitions to learn control policies, circumventing the need for potentially expensive or unsafe online data collection. Significant progress has been made recently in offline model-based reinforcement learning, appro... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "Model-based offline reinforcement learning algorithms typically involve constructing a pessimistic MDP, which is implemented based on an uncertainty estimation of the learned model. This paper conducts empirical analysis to compare different design choices of the uncertainty estimation in prac... |
zz9hXVhf40 | L1E57BlqSOY | 2,022 | Revisiting Design Choices in Offline Model Based Reinforcement Learning | Offline reinforcement learning enables agents to leverage large pre-collected datasets of environment transitions to learn control policies, circumventing the need for potentially expensive or unsafe online data collection. Significant progress has been made recently in offline model-based reinforcement learning, appro... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper provides an evaluation of many of the design choices and hyperparameter decisions made in offline model-based reinforcement learning methods which have emerged recently. Particularly, the empirical study looks at uncertainty penalties used in these methods, as well as hyperparameters... |
zz9hXVhf40 | pCMrUs15dnj | 2,022 | Revisiting Design Choices in Offline Model Based Reinforcement Learning | Offline reinforcement learning enables agents to leverage large pre-collected datasets of environment transitions to learn control policies, circumventing the need for potentially expensive or unsafe online data collection. Significant progress has been made recently in offline model-based reinforcement learning, appro... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The authors present an empirical study of several uncertainty quantification heuristics applied to model learning in offline model-based reinforcement learning. Specifically, they consider the basic architecture of MOPO, in which an uncertainty based state-action penalty function is applied on... |
zz9hXVhf40 | 7QJWP1izpM4 | 2,022 | Revisiting Design Choices in Offline Model Based Reinforcement Learning | Offline reinforcement learning enables agents to leverage large pre-collected datasets of environment transitions to learn control policies, circumventing the need for potentially expensive or unsafe online data collection. Significant progress has been made recently in offline model-based reinforcement learning, appro... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
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- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper provides detailed analysis of different uncertainty quantifications in Model-based offline RL, from both statistical and empirical perspectives. Further, the paper performs Bayesian optimization to find hyper-parameters and the optimized hyper-parameters perform better empirically. \... |
zyrhwrd9EYs | -aEdXoBehI4 | 2,022 | To Impute or Not To Impute? Missing Data in Treatment Effect Estimation | Missing data is a systemic problem in practical scenarios that causes noise and bias when estimating treatment effects. This makes treatment effect estimation from data with missingness a particularly tricky endeavour. A key reason for this is that standard assumptions on missingness are rendered insufficient due to th... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
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- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "\"we identify a new missingness mechanism, which we term mixed confounded missingness (MCM), where some missingness determines treatment selection and other missingness is determined by treatment selection.\"\n\nThe author gave a new term called “MCM” which is not something new. MCM is a type ... |
zyrhwrd9EYs | Sw15Q7x-eNY | 2,022 | To Impute or Not To Impute? Missing Data in Treatment Effect Estimation | Missing data is a systemic problem in practical scenarios that causes noise and bias when estimating treatment effects. This makes treatment effect estimation from data with missingness a particularly tricky endeavour. A key reason for this is that standard assumptions on missingness are rendered insufficient due to th... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper studies dealing with missing values in estimating treatment effects. Authors identify a new missingness mechanism, mixed confounded missingness (MCM), including missingness that determines treatment selection and missingness that is determined by treatment selection. The authors sho... |
zyrhwrd9EYs | vop8d7q0nC4 | 2,022 | To Impute or Not To Impute? Missing Data in Treatment Effect Estimation | Missing data is a systemic problem in practical scenarios that causes noise and bias when estimating treatment effects. This makes treatment effect estimation from data with missingness a particularly tricky endeavour. A key reason for this is that standard assumptions on missingness are rendered insufficient due to th... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "In this paper, the authors mainly study the problem of missing data in treatment effect estimation and highlight the importance of addressing this problem. The authors propose a selective imputation scheme which is more well suited for addressing missingness in such scenarios. Authors also pre... |
zxEfpcmTDnF | zuD4vNVLIxz | 2,022 | Learning and controlling the source-filter representation of speech with a variational autoencoder | Understanding and controlling latent representations in deep generative models is a challenging yet important problem for analyzing, transforming and generating various types of data. In speech processing, inspiring from the anatomical mechanisms of phonation, the source-filter model considers that speech signals are p... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper shows that the fundamental frequency and formant frequency information is encoded in a speech VAE model.\nThis can be found by using artificially controlled/generated dataset.\nAfter finding how to manipulate the latent space, one can control arbitrary speech samples in a desirable ... |
zxEfpcmTDnF | z-B1OnWOtp_ | 2,022 | Learning and controlling the source-filter representation of speech with a variational autoencoder | Understanding and controlling latent representations in deep generative models is a challenging yet important problem for analyzing, transforming and generating various types of data. In speech processing, inspiring from the anatomical mechanisms of phonation, the source-filter model considers that speech signals are p... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper analyzes the latent representations of speech spectrograms learned by unsupervised variational autoencoders (VAEs) and discovers that the VAE learns to model the variation of fundamental frequencies (F0/source) and formant frequencies (filters) using orthogonal subspaces. Based on t... |
zxEfpcmTDnF | 56VxUr-PO5h | 2,022 | Learning and controlling the source-filter representation of speech with a variational autoencoder | Understanding and controlling latent representations in deep generative models is a challenging yet important problem for analyzing, transforming and generating various types of data. In speech processing, inspiring from the anatomical mechanisms of phonation, the source-filter model considers that speech signals are p... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper proposes a method for utilizing labeled synthetic data in order to characterize and control the latent space of a VAE trained on individual frames of speech spectrograms.\nKey properties of the data which one might want explicit control over are identified, i.e., pitch and formant fr... |
zxEfpcmTDnF | DmvCsvKK-C0 | 2,022 | Learning and controlling the source-filter representation of speech with a variational autoencoder | Understanding and controlling latent representations in deep generative models is a challenging yet important problem for analyzing, transforming and generating various types of data. In speech processing, inspiring from the anatomical mechanisms of phonation, the source-filter model considers that speech signals are p... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper analyzes VAE latent embeddings to extract subspaces that relate to pitch (f0) and formant frequencies (f1 through fN). This is done through first training a frame-synchronous IS-VAE model from clean speech data. The authors pass controlled synthesized speech through the model and o... |
zuqcmNVK4c2 | 4l7GAqeKj4I | 2,022 | Self-Joint Supervised Learning | Supervised learning is a fundamental framework used to train machine learning systems. A supervised learning problem is often formulated using an i.i.d. assumption that restricts model attention to a single relevant signal at a time when predicting. This contrasts with the human ability to actively use related samples ... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The Authors propose a new way of training classifier models. Instead of classifying each i.i.d. example independently during training and inference, they jointly classify a pair (X1, X2) of them, returning a joint distribution of labels (Y1, Y2). The loss function is modified so that the model... |
zuqcmNVK4c2 | bgq04xhGww | 2,022 | Self-Joint Supervised Learning | Supervised learning is a fundamental framework used to train machine learning systems. A supervised learning problem is often formulated using an i.i.d. assumption that restricts model attention to a single relevant signal at a time when predicting. This contrasts with the human ability to actively use related samples ... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper introduces a pairwise loss function for supervised learning, named self-joint learning. Instead of predicting the conditional distribution of the label given one data sample as in conventional supervised learning, the proposed self-joint learning framework predicts the conditional j... |
zuqcmNVK4c2 | 79tJyc2F8Dg | 2,022 | Self-Joint Supervised Learning | Supervised learning is a fundamental framework used to train machine learning systems. A supervised learning problem is often formulated using an i.i.d. assumption that restricts model attention to a single relevant signal at a time when predicting. This contrasts with the human ability to actively use related samples ... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "Paper propose a simple but effective method of learning. Feeding in a pair of data and learn the join conditional probabilities for predictions. The advantage is that the combination of data goes as the number of ways to partition the original data into pairs. This is a huge number.\n", "main_... |
zuDmDfeoB_1 | RQljuCcy-hp | 2,022 | How Does the Task Landscape Affect MAML Performance? | Model-Agnostic Meta-Learning (MAML) has become increasingly popular for training models that can quickly adapt to new tasks via one or few stochastic gradient descent steps. However, the MAML objective is significantly more difficult to optimize compared to standard non-adaptive learning (NAL), and little is understood... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The authors aim to compare theoretically and empirically the ability of MAML and Non-Adaptive Learning (NAL) to different tasks in a multi-task setting, where tasks are sampled independently from the same distribution. They argue that MAML is better suitable for adapting to hard tasks, while N... |
zuDmDfeoB_1 | XV8T-2YJQ4O | 2,022 | How Does the Task Landscape Affect MAML Performance? | Model-Agnostic Meta-Learning (MAML) has become increasingly popular for training models that can quickly adapt to new tasks via one or few stochastic gradient descent steps. However, the MAML objective is significantly more difficult to optimize compared to standard non-adaptive learning (NAL), and little is understood... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper analyzes the performance of MAML algorithm under linear regression setting and compares that with the NAL under the same tasks. The authors show that the excess risk is smaller if there is more discrepency in the hardness of tasks and if the optimal solutions of hard tasks locate cl... |
zuDmDfeoB_1 | nOMar2XTAK- | 2,022 | How Does the Task Landscape Affect MAML Performance? | Model-Agnostic Meta-Learning (MAML) has become increasingly popular for training models that can quickly adapt to new tasks via one or few stochastic gradient descent steps. However, the MAML objective is significantly more difficult to optimize compared to standard non-adaptive learning (NAL), and little is understood... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper is about finding the conditions under which MAML outperforms standard multi-task learning. In particular, the authors focus on a linear regression setting and show that MAML outperforms NAL under the following two conditions: (i) there must be some discrepancy in hardness among the ... |
zuDmDfeoB_1 | ofPS6AiV_fA | 2,022 | How Does the Task Landscape Affect MAML Performance? | Model-Agnostic Meta-Learning (MAML) has become increasingly popular for training models that can quickly adapt to new tasks via one or few stochastic gradient descent steps. However, the MAML objective is significantly more difficult to optimize compared to standard non-adaptive learning (NAL), and little is understood... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper analytically compares the excess risk of two meta-learning methods: MAML and NAL. NAL is the simple baseline where the initialization for optimizing the test tasks is learned as parameter which minimizes the average loss of train tasks. \n\n1. For a particular simple setting of line... |
zrdUVVAvcP2 | UJH91RO9uJl | 2,022 | GrASP: Gradient-Based Affordance Selection for Planning | Planning with a learned model is arguably a key component of intelligence. There are several challenges in realizing such a component in large-scale reinforcement learning (RL) problems. One such challenge is dealing effectively with continuous action spaces when using tree-search planning (e.g., it is not feasible to ... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper looks incorporating the concept of affordances from ecological psychology into the planning process. \nThe basic premise is that affordances represent the possible relevant actions available to an agent that are potentially moderated by their goals and the state of the world. This h... |
zrdUVVAvcP2 | 76m8u7dGlSC | 2,022 | GrASP: Gradient-Based Affordance Selection for Planning | Planning with a learned model is arguably a key component of intelligence. There are several challenges in realizing such a component in large-scale reinforcement learning (RL) problems. One such challenge is dealing effectively with continuous action spaces when using tree-search planning (e.g., it is not feasible to ... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper proposes a gradient-based method for selecting affordances in planning. Specifically, it includes an affordance module that maps state representations to continuous actions/options. The planning procedure is aided by a learned model with an encoding, dynamics, reward, and value modu... |
zrdUVVAvcP2 | FCEjZlR6Vs7 | 2,022 | GrASP: Gradient-Based Affordance Selection for Planning | Planning with a learned model is arguably a key component of intelligence. There are several challenges in realizing such a component in large-scale reinforcement learning (RL) problems. One such challenge is dealing effectively with continuous action spaces when using tree-search planning (e.g., it is not feasible to ... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper proposes a gradient-based affordance selection, i.e., action/option selection, in addition to the value equivalent modules for tree-expansion procedure(s) in planning.\nThe claim is that GrASP can learn primitive-action and option selection and plan in a continuous state and action s... |
zrdUVVAvcP2 | Nd4K1G4XxCn | 2,022 | GrASP: Gradient-Based Affordance Selection for Planning | Planning with a learned model is arguably a key component of intelligence. There are several challenges in realizing such a component in large-scale reinforcement learning (RL) problems. One such challenge is dealing effectively with continuous action spaces when using tree-search planning (e.g., it is not feasible to ... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper proposes dealing with tree search planning in continuous action spaces by learning affordances.\nThe authors propose an architecture composed of several modules, where they are able to plan ahead in a tree search manner by learning a module that expands K discrete possible affordance... |
zrW-LVXj2k1 | aCkK65KHdrt | 2,022 | On the benefits of maximum likelihood estimation for Regression and Forecasting | We advocate for a practical Maximum Likelihood Estimation (MLE) approach towards designing loss functions for regression and forecasting, as an alternative to the typical approach of direct empirical risk minimization on a specific target metric. The MLE approach is better suited to capture inductive biases such as pri... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper promotes the maximum likelihood estimation over target metric optimization. The main theoretical results is a finite sample error bound. Specific examples and numerical results are provide to further illustrate the investigation.", "main_review": "Strengths:\n\n- It is well known th... |
zrW-LVXj2k1 | mWSbEDbEHf | 2,022 | On the benefits of maximum likelihood estimation for Regression and Forecasting | We advocate for a practical Maximum Likelihood Estimation (MLE) approach towards designing loss functions for regression and forecasting, as an alternative to the typical approach of direct empirical risk minimization on a specific target metric. The MLE approach is better suited to capture inductive biases such as pri... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper compares two inferential methods for regression models, the maximum likelihood estimation and the estimation based on loss functions. For that purpose, a quantity is proposed to measure the correctness of an estimator of a regression model. Then it is shown that, under certain condi... |
zrW-LVXj2k1 | SZL-7j70hED | 2,022 | On the benefits of maximum likelihood estimation for Regression and Forecasting | We advocate for a practical Maximum Likelihood Estimation (MLE) approach towards designing loss functions for regression and forecasting, as an alternative to the typical approach of direct empirical risk minimization on a specific target metric. The MLE approach is better suited to capture inductive biases such as pri... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper provides theoretical results that favor MLE estimators, in terms of the excess square loss risk, compared to empirical risk estimators under mild assumption. In particular, the paper devises an estimator for Poisson regression and employs an existing estimator for heavy-tail Pareto ... |
zq1iJkNk3uN | NfwmpnGvw_s | 2,022 | Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm | Recently, large-scale Contrastive Language-Image Pre-training (CLIP) has attracted unprecedented attention for its impressive zero-shot recognition ability and excellent transferability to downstream tasks. However, CLIP is quite data-hungry and requires 400M image-text pairs for pre-training, thereby restricting its a... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper proposes a data-efficient CLIP (DeCLIP) by employing three additional objectives:\n\n- (1) self-supervision within each modality (e.g., vision domain => SimSiam, text domain => masked language model as BERT)\n- (2) Multi-view supervision (e.g., resize random crop for vision modality... |
zq1iJkNk3uN | AZrxIVnuhYG | 2,022 | Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm | Recently, large-scale Contrastive Language-Image Pre-training (CLIP) has attracted unprecedented attention for its impressive zero-shot recognition ability and excellent transferability to downstream tasks. However, CLIP is quite data-hungry and requires 400M image-text pairs for pre-training, thereby restricting its a... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper proposes DeCLIP to further utilize the data potential by adding three training objectives to CLIP pre-training: 1) inspired by SimSiam and BERT, self-supervised objectives are added to both image and text; 2) they generate different views for both images and text, and apply contrasti... |
zq1iJkNk3uN | C7eEUbcCVI | 2,022 | Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm | Recently, large-scale Contrastive Language-Image Pre-training (CLIP) has attracted unprecedented attention for its impressive zero-shot recognition ability and excellent transferability to downstream tasks. However, CLIP is quite data-hungry and requires 400M image-text pairs for pre-training, thereby restricting its a... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper proposes DeCLIP with three additions to the original CLIP model: (1) single-modal self supervised pre-training; (2) cross-modal contrastive pretraining across multiple views and (3) cross-modal contrastive pretraining across nearest neighbors in feature space. DeCLIP is able to ach... |
zq1iJkNk3uN | NkaP4s_2Iip | 2,022 | Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm | Recently, large-scale Contrastive Language-Image Pre-training (CLIP) has attracted unprecedented attention for its impressive zero-shot recognition ability and excellent transferability to downstream tasks. However, CLIP is quite data-hungry and requires 400M image-text pairs for pre-training, thereby restricting its a... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "In this paper, the authors mitigate the data-hungriness of the CLIP model. The authors propose three directions: single-modality self-supervision; multi-view multi-modality contrastive learning, and nearest-neighbor supervision. With the proposed three components, the authors can achieve bette... |
ziRLU3Y2PN_ | ytBwwamJO4 | 2,022 | Generalized rectifier wavelet covariance models for texture synthesis | State-of-the-art maximum entropy models for texture synthesis are built from statistics relying on image representations defined by convolutional neural networks (CNN). Such representations capture rich structures in texture images, outperforming wavelet-based representations in this regard. However, conversely to neur... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper presents a novel image texture model that is a hybrid of the traditional wavelet constructions, and the more modern machine learning constructions (incorporating only ReLU nonlinearities on the wavelet basis), proves that this class of models is actually akin to phase harmonic functi... |
ziRLU3Y2PN_ | ScFNCi7rzei | 2,022 | Generalized rectifier wavelet covariance models for texture synthesis | State-of-the-art maximum entropy models for texture synthesis are built from statistics relying on image representations defined by convolutional neural networks (CNN). Such representations capture rich structures in texture images, outperforming wavelet-based representations in this regard. However, conversely to neur... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper presents a new image representation model based on wavelets and non-linear rectifiers that allows to synthesize complex geometric textures with a better visual quality than previous wavelet-based models. \nThe main interest of the paper is the usage of the mathematical results from ... |
ziRLU3Y2PN_ | Jp6u6L1toBT | 2,022 | Generalized rectifier wavelet covariance models for texture synthesis | State-of-the-art maximum entropy models for texture synthesis are built from statistics relying on image representations defined by convolutional neural networks (CNN). Such representations capture rich structures in texture images, outperforming wavelet-based representations in this regard. However, conversely to neur... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper provides an attempt to characterize wavelet-based texture synthesis models contingent on the number of parameters and the nature of the parametrization. Proper baselines are added with respect to other relevant texture synthesis models.", "main_review": "This is a paper that has a g... |
ziRLU3Y2PN_ | e1_L1peKpQf | 2,022 | Generalized rectifier wavelet covariance models for texture synthesis | State-of-the-art maximum entropy models for texture synthesis are built from statistics relying on image representations defined by convolutional neural networks (CNN). Such representations capture rich structures in texture images, outperforming wavelet-based representations in this regard. However, conversely to neur... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This work proposed a texture synthesis framework using the rectified wavelet coefficients. The paper claims that the proposed method cand achieve similar quality with the VGG feature based method (Gatys et al. 22015) and random filter based method (RF, Ustyuzhaninov et al 2017) and gets better... |
zhynF6JnC4q | 56sR7wcCboW | 2,022 | Adaptive Q-learning for Interaction-Limited Reinforcement Learning | Conventional reinforcement learning (RL) needs an environment to collect fresh data, which is impractical when an online interaction is costly.
Offline RL provides an alternative solution by directly learning from the logged dataset. However, it usually yields unsatisfactory performance due to a pessimistic update sche... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper tackles a variation to the offline RL setting, where the agent is allowed some limited number of online interaction steps after learning offline. An algorithm, CGQL, is proposed for this setting and uses the idea that online and offline data should be used in different updates. Expe... |
zhynF6JnC4q | O1PzZV75LFC | 2,022 | Adaptive Q-learning for Interaction-Limited Reinforcement Learning | Conventional reinforcement learning (RL) needs an environment to collect fresh data, which is impractical when an online interaction is costly.
Offline RL provides an alternative solution by directly learning from the logged dataset. However, it usually yields unsatisfactory performance due to a pessimistic update sche... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper proposes GCQL, a new RL algorithm that is trained on a mixture of offline data and online interactions. The novel component of the algorithm is a reweighting that balances acting pessimistically on offline data and greedily on online interactions. The authors propose a mixture replay... |
zhynF6JnC4q | JCEmdwY_Wjr | 2,022 | Adaptive Q-learning for Interaction-Limited Reinforcement Learning | Conventional reinforcement learning (RL) needs an environment to collect fresh data, which is impractical when an online interaction is costly.
Offline RL provides an alternative solution by directly learning from the logged dataset. However, it usually yields unsatisfactory performance due to a pessimistic update sche... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The authors propose a mixed offline-online RL approach for which they design an algorithm. They propose to maintain 2 separate replay buffers, one for online data and one for offline data, to allow them to sample either an online or offline batch of data when doing an update step, and tailor t... |
zhynF6JnC4q | Y8px7UNV0Ma | 2,022 | Adaptive Q-learning for Interaction-Limited Reinforcement Learning | Conventional reinforcement learning (RL) needs an environment to collect fresh data, which is impractical when an online interaction is costly.
Offline RL provides an alternative solution by directly learning from the logged dataset. However, it usually yields unsatisfactory performance due to a pessimistic update sche... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper presents a framework called adaptive Q-learning that integrates the advantage of offline learning and online learning. ", "main_review": "Poor writing. Inadequate experiments design. This paper, at its current status, is not ready to be submitted to conferences like ICLR. \nActionab... |
zfmB5vgfaCt | lTB9JBrm6yN | 2,022 | TransSlowDown: Efficiency Attacks on Neural Machine Translation Systems | Neural machine translation (NMT) systems have received massive attention from academia and industry. Despite a rich set of work focusing on improving NMT systems’ accuracy, the less explored topic of efficiency is also important to NMT systems because of the real-time demand of translation applications. In this paper,... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "TransSlowDown is an attack scheme that aims to targets the computational resources of NMT systems. The authors show that small modifications to benign input sentences can significantly increase the computation NMT needs to process the input, paving the way for denial-of-service attacks on tran... |
zfmB5vgfaCt | h5gbQwiJKf | 2,022 | TransSlowDown: Efficiency Attacks on Neural Machine Translation Systems | Neural machine translation (NMT) systems have received massive attention from academia and industry. Despite a rich set of work focusing on improving NMT systems’ accuracy, the less explored topic of efficiency is also important to NMT systems because of the real-time demand of translation applications. In this paper,... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper proposes an adversarial attack method for NMT, aiming to increase the computation complexity while decoding by introducing perturbations into the input. To achieve that, the authors propose an attacking algorithm that consists of three steps: find the most important source token w.r.... |
zfmB5vgfaCt | p_UyKCZ2gm | 2,022 | TransSlowDown: Efficiency Attacks on Neural Machine Translation Systems | Neural machine translation (NMT) systems have received massive attention from academia and industry. Despite a rich set of work focusing on improving NMT systems’ accuracy, the less explored topic of efficiency is also important to NMT systems because of the real-time demand of translation applications. In this paper,... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper focuses on the efficiency of neural machine translation (NMT) systems, proposing a novel attack approach to test the efficiency robustness. The attack approach can be divided into three parts: 1) find the most relevant tokens of inference efficiency; 2) generate adversarial perturba... |
zfmB5vgfaCt | V4GCz4JuZKn | 2,022 | TransSlowDown: Efficiency Attacks on Neural Machine Translation Systems | Neural machine translation (NMT) systems have received massive attention from academia and industry. Despite a rich set of work focusing on improving NMT systems’ accuracy, the less explored topic of efficiency is also important to NMT systems because of the real-time demand of translation applications. In this paper,... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper considers to attack an NMT system from the perspective of efficiency. At a high level, it aims to slightly modify the input such that the target NMT system outputs a long translation, leading to decreased decoding efficiency. To this end, it proposes a method to guide the input modi... |
zf_Ll3HZWgy | goW9aCwyBsi | 2,022 | How Much Can CLIP Benefit Vision-and-Language Tasks? | Most existing Vision-and-Language (V&L) models rely on pre-trained visual encoders, using a relatively small set of manually-annotated data (as compared to web-crawled data), to perceive the visual world. However, it has been observed that large-scale pretraining usually can result in better generalization performance,... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper explores how features from CLIP (Contrastive Language-Image Pre-training, Radford et al., 2021) affect the performance of vision-and-language models across a series of tasks. The authors explore using CLIP as a visual encoder in two settings, plugging its features directly into task... |
zf_Ll3HZWgy | 2Td7wH2eG1C | 2,022 | How Much Can CLIP Benefit Vision-and-Language Tasks? | Most existing Vision-and-Language (V&L) models rely on pre-trained visual encoders, using a relatively small set of manually-annotated data (as compared to web-crawled data), to perceive the visual world. However, it has been observed that large-scale pretraining usually can result in better generalization performance,... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper performs empirical analyses of applying the CLIP to various vision-and-language tasks. It demonstrates the potentials of the model in generalizing to different downstream applications, and provides some suggestions for model deployment. Experimental results show that CLIP pretrainin... |
zf_Ll3HZWgy | v8_ecERXcu1 | 2,022 | How Much Can CLIP Benefit Vision-and-Language Tasks? | Most existing Vision-and-Language (V&L) models rely on pre-trained visual encoders, using a relatively small set of manually-annotated data (as compared to web-crawled data), to perceive the visual world. However, it has been observed that large-scale pretraining usually can result in better generalization performance,... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper examines how well CLIP's visual encoders are transferred on vision-and-language (VL) tasks. \nThe paper conducted three without-VLP tasks: VQA, image captioning, and vision-and-language navigation, and three with-VLP tasks: VQA, SNLI-VE, and GQA to show CLIP's visual encoders' tran... |
zf_Ll3HZWgy | 1DmrJVOqcOz | 2,022 | How Much Can CLIP Benefit Vision-and-Language Tasks? | Most existing Vision-and-Language (V&L) models rely on pre-trained visual encoders, using a relatively small set of manually-annotated data (as compared to web-crawled data), to perceive the visual world. However, it has been observed that large-scale pretraining usually can result in better generalization performance,... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper utilizes recently proposed CLIP-ResNet/ViT visual encoders instead of the standard backbones to conduct a large-scale empirical study for several vision and language tasks. The experimental setup aims to answer the question in the title of this paper by conducting 1) the task-specifi... |
zeGpMIt6Pfq | qa2JJrYDc0R | 2,022 | BioLCNet: Reward-modulated Locally Connected Spiking Neural Networks | Recent studies have shown that convolutional neural networks (CNNs) are not the only feasible solution for image classification. Furthermore, weight sharing and backpropagation used in CNNs do not correspond to the mechanisms present in the primate visual system. To propose a more biologically plausible solution, we de... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper presents a spiking neural network (SNN) architecture for\nimage classification, designed to be more biologically plausible than\ncomparable existing architectures. In particular, it eschews\nconvolutional connectivity in favour of local connectivity, and uses\nSTDP (vanilla and rewa... |
zeGpMIt6Pfq | iBhvOdLkInX | 2,022 | BioLCNet: Reward-modulated Locally Connected Spiking Neural Networks | Recent studies have shown that convolutional neural networks (CNNs) are not the only feasible solution for image classification. Furthermore, weight sharing and backpropagation used in CNNs do not correspond to the mechanisms present in the primate visual system. To propose a more biologically plausible solution, we de... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The authors proposed an SNN model, dubbed BioLCNet, for image classification. The proposed network consists of three layers: 1) input layer, accepting spike trains as input; 2) locally connected (LC) hidden layer; 3) decoding fully connected (FC) output layer. The LC layer is for feature extr... |
zeGpMIt6Pfq | N5qHlNdlir0 | 2,022 | BioLCNet: Reward-modulated Locally Connected Spiking Neural Networks | Recent studies have shown that convolutional neural networks (CNNs) are not the only feasible solution for image classification. Furthermore, weight sharing and backpropagation used in CNNs do not correspond to the mechanisms present in the primate visual system. To propose a more biologically plausible solution, we de... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper discusses learning in biological networks, and proposes a model that combines spiking networks, local connections (convolutions without weight sharing) and reward-modulated spike-timing dependent plasticity. All three components are chosen to be more realistic compared to artificial ... |
zbZL1s-pBF | 5vLBaGy_LYG | 2,022 | Training-Free Robust Multimodal Learning via Sample-Wise Jacobian Regularization | Multimodal fusion emerges as an appealing technique to improve model performances on many tasks. Nevertheless, the robustness of such fusion methods is rarely involved in the present literature. In this paper, we are the first to propose a training-free robust late-fusion method by exploiting conditional independence a... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper propses a late-fusion algorithm for multimodal learning. This algorithm serves to improve the robustness against adversarial attacks and random corruptions. Assuming that which modality is perturbed, this paper propses to leverage Jacobian regularization and conditional independence... |
zbZL1s-pBF | HPDioUk70I6 | 2,022 | Training-Free Robust Multimodal Learning via Sample-Wise Jacobian Regularization | Multimodal fusion emerges as an appealing technique to improve model performances on many tasks. Nevertheless, the robustness of such fusion methods is rarely involved in the present literature. In this paper, we are the first to propose a training-free robust late-fusion method by exploiting conditional independence a... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "In this paper, the authors proposed a training-free late-fusion method for robust multimodal learning. They specifically considering its performance under adversarial attacks and random corruptions which usually confuse the model by introducing noise to the input data. To promote the multimoda... |
zbZL1s-pBF | eNjwwnLrxRR | 2,022 | Training-Free Robust Multimodal Learning via Sample-Wise Jacobian Regularization | Multimodal fusion emerges as an appealing technique to improve model performances on many tasks. Nevertheless, the robustness of such fusion methods is rarely involved in the present literature. In this paper, we are the first to propose a training-free robust late-fusion method by exploiting conditional independence a... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper proposed a training-free robust multimodal learning late-fusion methods via sample-wise Jacobian regularization. The key idea of the work is to minimize the Frobenius norm of a Jacobian matrix, so that the multimodal prediction is stabilized. The paper demonstrate\nthe good efficacy ... |
zaALYtvbRlH | XoUHF965-h8 | 2,022 | SpanDrop: Simple and Effective Counterfactual Learning for Long Sequences | Distilling supervision signal from a long sequence to make predictions is a challenging task in machine learning, especially when not all elements in the input sequence contribute equally to the desired output. In this paper, we propose SpanDrop, a simple and effective data augmentation technique that helps models iden... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "In this paper, we instead investigate learning problems for long sequences where not all input elements contribute equally to the desired output. SCANDROP is a simple algorithm to randomly drop segments in a sequence. The authors first establish that when the number of contributing segments is... |
zaALYtvbRlH | FzzbMZ14-LE | 2,022 | SpanDrop: Simple and Effective Counterfactual Learning for Long Sequences | Distilling supervision signal from a long sequence to make predictions is a challenging task in machine learning, especially when not all elements in the input sequence contribute equally to the desired output. In this paper, we propose SpanDrop, a simple and effective data augmentation technique that helps models iden... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper focuses on distilling supervision signal from long sequences. They focus on cases where the input is a long sequence of length n, but the target prediction is determined by a small subset of size m of sequence fragments, where m << n. The authors propose augmenting data by randomly d... |
zaALYtvbRlH | 9kJd9LkP5k | 2,022 | SpanDrop: Simple and Effective Counterfactual Learning for Long Sequences | Distilling supervision signal from a long sequence to make predictions is a challenging task in machine learning, especially when not all elements in the input sequence contribute equally to the desired output. In this paper, we propose SpanDrop, a simple and effective data augmentation technique that helps models iden... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This work proposes SPANDROP, a simple variant of dropout, working on the spans of long sequences. SPANDROP randomly ablates parts of a sequence at a time and asks the model to perform the same task to emulate counterfactual learning and achieve input attribution. The method is tested on both t... |
zaALYtvbRlH | 5SONjJQCFcx | 2,022 | SpanDrop: Simple and Effective Counterfactual Learning for Long Sequences | Distilling supervision signal from a long sequence to make predictions is a challenging task in machine learning, especially when not all elements in the input sequence contribute equally to the desired output. In this paper, we propose SpanDrop, a simple and effective data augmentation technique that helps models iden... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper proposes a data augmentation method, SpanDrop (and its variant Beta-SpanDrop), for long sequence data, especially where supporting facts take small portions. They provide a theoretical background on their method and evaluate the method on a synthetic task (FindCats) and four real na... |
zXne1klXIQ | _ChCHY2Eycq | 2,022 | Improving Out-of-Distribution Robustness via Selective Augmentation | Machine learning algorithms typically assume that training and test examples are drawn from the same distribution. However, distribution shifts is a common problem in real-world applications and can cause models to perform dramatically worse at test time. In this paper, we specifically consider the problems of domain s... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "Authors introduced approaches aimed at learning invariant predictors across data sources. Rather than using distribution/risk matching schemes as often done by previous work, they propose to train models against mixtures of data points as a means to avoid that models rely on spurious correlati... |
zXne1klXIQ | AIjTwOXgDz_ | 2,022 | Improving Out-of-Distribution Robustness via Selective Augmentation | Machine learning algorithms typically assume that training and test examples are drawn from the same distribution. However, distribution shifts is a common problem in real-world applications and can cause models to perform dramatically worse at test time. In this paper, we specifically consider the problems of domain s... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper considers the model robustness under distribution shift brought by domains and subpopulations. Specifically, based on the interpolation scheme in mixup, the authors propose two selection strategies to perform data augmentation, aim at eliminating the spurious correlations and learnin... |
zXne1klXIQ | ZU9Dq3GC-Xp | 2,022 | Improving Out-of-Distribution Robustness via Selective Augmentation | Machine learning algorithms typically assume that training and test examples are drawn from the same distribution. However, distribution shifts is a common problem in real-world applications and can cause models to perform dramatically worse at test time. In this paper, we specifically consider the problems of domain s... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper propose a mixup-style data augmentation method under the data distribution shift context. In particular, data distributions are formulated as mixture of distributions (i.e., domains), and two distribution shift scenarios are considered: (1) domain shift, where the test domain and tr... |
zXM0b4hi5_B | XEhGsithtlc | 2,022 | On the relation between statistical learning and perceptual distances | It has been demonstrated many times that the behavior of the human visual system is connected to the statistics of natural images. Since machine learning relies on the statistics of training data as well, the above connection has interesting implications when using perceptual distances (which mimic the behavior of the ... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper presents a mainly theoretical explication of the relationship between natural image statistics and perceptual distances for small image distortions. The paper presents a number of observations linking distances in natural images, autoencoders, and perceptual similarity for humans. T... |
zXM0b4hi5_B | 1ug4LiQ4hLn | 2,022 | On the relation between statistical learning and perceptual distances | It has been demonstrated many times that the behavior of the human visual system is connected to the statistics of natural images. Since machine learning relies on the statistics of training data as well, the above connection has interesting implications when using perceptual distances (which mimic the behavior of the ... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The authors present few relation between statistical learning and perceptual distances. Specifically, they explain that\n\n1. perceptual distances correlate with image likelihoods;\n2. auto-encoder latent space induced distances of natural images are correlated with training data probability a... |
zXM0b4hi5_B | h2Z0NhoA5CM | 2,022 | On the relation between statistical learning and perceptual distances | It has been demonstrated many times that the behavior of the human visual system is connected to the statistics of natural images. Since machine learning relies on the statistics of training data as well, the above connection has interesting implications when using perceptual distances (which mimic the behavior of the ... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "\nThe work presented in this paper aims to analyze the relationships between the probability distribution of the data, perceptual\ndistances, and unsupervised machine learning. Perceptual sensitivity is correlated with the probability of an image \nin its close neighborhood. The paper also exp... |
zXM0b4hi5_B | O92p9ItcWyE | 2,022 | On the relation between statistical learning and perceptual distances | It has been demonstrated many times that the behavior of the human visual system is connected to the statistics of natural images. Since machine learning relies on the statistics of training data as well, the above connection has interesting implications when using perceptual distances (which mimic the behavior of the ... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "Interesting (but debatable) observations between image prior, image quality, and perceptual distances.", "main_review": "Strengths:\n\nThe authors investigate a very interesting and important problem that lies in the intersection between perception and statistics.\n\nWeaknesses:\n\nFor Observa... |
zU2v47WF0Ku | etJIqhCK7Sw | 2,022 | Implicit Bias of Linear Equivariant Networks | Group equivariant convolutional neural networks (G-CNNs) are generalizations of convolutional neural networks (CNNs) which excel in a wide range of scientific and technical applications by explicitly encoding particular group symmetries, such as rotations and permutations, in their architectures. Although the success o... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "Group Equivariant CNNs (G-CNNs) generalize CNNs from the translation group to arbitrary groups. It has been shown that overparameterized/undetermined linear transformations and linear CNNs learned by gradient descent are implicitly biased, in that they find zero train loss solutions that minim... |
zU2v47WF0Ku | 7gKDTygP2n- | 2,022 | Implicit Bias of Linear Equivariant Networks | Group equivariant convolutional neural networks (G-CNNs) are generalizations of convolutional neural networks (CNNs) which excel in a wide range of scientific and technical applications by explicitly encoding particular group symmetries, such as rotations and permutations, in their architectures. Although the success o... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper describes a theoretical analysis of the implicit bias in G-CNNs. The results show that for linear G-CNNs trained on linearly separable data using GD converge to sparse solutions in the Fourier domain (equivalently dense solutions in the real domain). The theory is theoretically confi... |
zU2v47WF0Ku | Xevn5xmUQ7f | 2,022 | Implicit Bias of Linear Equivariant Networks | Group equivariant convolutional neural networks (G-CNNs) are generalizations of convolutional neural networks (CNNs) which excel in a wide range of scientific and technical applications by explicitly encoding particular group symmetries, such as rotations and permutations, in their architectures. Although the success o... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper studies the induced bias of gradient descent on L-layer linear group-equivariant convolutional neural networks. Their main result is: gradient descent implicitly controls the 2/L-Schatten norm of the Fourier transform of the (linear) predictor. More precisely, they show that gradien... |
zU2v47WF0Ku | tsWTCG-eUEJ | 2,022 | Implicit Bias of Linear Equivariant Networks | Group equivariant convolutional neural networks (G-CNNs) are generalizations of convolutional neural networks (CNNs) which excel in a wide range of scientific and technical applications by explicitly encoding particular group symmetries, such as rotations and permutations, in their architectures. Although the success o... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "Because of the explicit inductive bias of G-CNN, other inductive biases have not been discussed much.\nIn this paper, the author focuses on and analyzes the non-explicit inductive bias of G-CNNs.\nTechnically, they present the non-explicit bias in terms of Fourier matrices by using a group Fou... |
zRb7IWkTZAU | ageyidlqlb1 | 2,022 | Zero-Shot Reward Specification via Grounded Natural Language | Reward signals in reinforcement learning can be expensive signals in many tasks and often require access to direct state. The alternative to reward signals are usually demonstrations or goal images which can be labor intensive to collect. Goal text description is a low effort way of communicating the desired task. Goal... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper presents a hybrid learning/rule-based approach to language-conditioned reward specification, particularly for robotic control tasks from images. The core contribution of the work is in specifying the reward 0-shot. Specifically, the method parses a language instruction into an object... |
zRb7IWkTZAU | XRmBKWKTXYY | 2,022 | Zero-Shot Reward Specification via Grounded Natural Language | Reward signals in reinforcement learning can be expensive signals in many tasks and often require access to direct state. The alternative to reward signals are usually demonstrations or goal images which can be labor intensive to collect. Goal text description is a low effort way of communicating the desired task. Goal... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper demonstrates how to use pretrained CLIP model as a reward function for an RL agent. This approach enables flexible goal specification using language. The proposed reward generation method uses CLIP to identify the relevant objects and a separate module to compute the reward based on... |
zRb7IWkTZAU | OsW_FKM_UuA | 2,022 | Zero-Shot Reward Specification via Grounded Natural Language | Reward signals in reinforcement learning can be expensive signals in many tasks and often require access to direct state. The alternative to reward signals are usually demonstrations or goal images which can be labor intensive to collect. Goal text description is a low effort way of communicating the desired task. Goal... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper proposes a framework to train policies for tasks that are specified via language text without the use of any expert trajectories or underlying state information to engineer reward functions. The authors leverage a state-of-the-art visual grounding model (CLIP) to ground object nouns ... |
zRb7IWkTZAU | Sf9J7hCAU5h | 2,022 | Zero-Shot Reward Specification via Grounded Natural Language | Reward signals in reinforcement learning can be expensive signals in many tasks and often require access to direct state. The alternative to reward signals are usually demonstrations or goal images which can be labor intensive to collect. Goal text description is a low effort way of communicating the desired task. Goal... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper proposes an approach for zero-shot reward specification using natural language groundings without expert demos and state information. The work proposes using CLIP’s image+language encoder to find the saliency maps and separately encoding the target locations for the object. These obj... |
zRJu6mU2BaE | fyl7sNm1Rm | 2,022 | ConFeSS: A Framework for Single Source Cross-Domain Few-Shot Learning | Most current few-shot learning methods train a model from abundantly labeled base category data and then transfer and adapt the model to sparsely labeled novel category data. These methods mostly generalize well on novel categories from the same domain as the base categories but perform poorly for distant domain catego... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The problem is to learn by few shots (FSL) when the final domain is highly distant from the source base (i.e. natural, medical and satellite), dubbed single source cross-domain few-shot learning. In short, the approach consists of three steps: 1) train a feature extracting backbone with the co... |
zRJu6mU2BaE | RH5ZPeNj99_ | 2,022 | ConFeSS: A Framework for Single Source Cross-Domain Few-Shot Learning | Most current few-shot learning methods train a model from abundantly labeled base category data and then transfer and adapt the model to sparsely labeled novel category data. These methods mostly generalize well on novel categories from the same domain as the base categories but perform poorly for distant domain catego... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper proposes a framework, terms as ConFeSS, for dealing with cross-domain few-shot learning problems. Specifically, it firstly trains a feature extracting backbone with the contrastive loss on the base category data for learning better features. Then, it trains a masking module to selec... |
zRJu6mU2BaE | tHfwJoFGnPr | 2,022 | ConFeSS: A Framework for Single Source Cross-Domain Few-Shot Learning | Most current few-shot learning methods train a model from abundantly labeled base category data and then transfer and adapt the model to sparsely labeled novel category data. These methods mostly generalize well on novel categories from the same domain as the base categories but perform poorly for distant domain catego... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "In this paper, the authors propose a generic framework for cross-domain few-shot learning. There are three steps: 1. Pre-training the backbone unsupervisedly using a self-supervised contrastive loss. 2. Select relevant features via a mask module. 3. Fine-tune the network with the selected feat... |
zRJu6mU2BaE | 0fOk7rrmJxG | 2,022 | ConFeSS: A Framework for Single Source Cross-Domain Few-Shot Learning | Most current few-shot learning methods train a model from abundantly labeled base category data and then transfer and adapt the model to sparsely labeled novel category data. These methods mostly generalize well on novel categories from the same domain as the base categories but perform poorly for distant domain catego... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper proposes a framework for cross-domain few-shot learning. The framework consists of three steps: 1) pre-training backbone; 2) meta-learn the feature masking network; 3) fine-tuning on target domain. Experiments on the CDFSL dataset show this framework outperforms SOTA methods. ", "ma... |
zPLQSnfd14w | bAqMulVpkzN | 2,022 | Two Regimes of Generalization for Non-Linear Metric Learning | A common approach to metric learning is to seek an embedding of the input data that behaves well with respect to the labels. While generalization bounds for linear embeddings are known, the non-linear case is not well understood. In this work we fill this gap by
providing uniform generalization guarantees for the cas... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "In this paper, the authors look at the Rademacher complexity of the family of Euclidean metrics learned on a data set via an $L$ layer network where the activations functions are Lipschitz. The idea behind the proof is to use the bounds for $\\epsilon$ net for the embedding network from Barlet... |
zPLQSnfd14w | 7MwP7ZcuVDI | 2,022 | Two Regimes of Generalization for Non-Linear Metric Learning | A common approach to metric learning is to seek an embedding of the input data that behaves well with respect to the labels. While generalization bounds for linear embeddings are known, the non-linear case is not well understood. In this work we fill this gap by
providing uniform generalization guarantees for the cas... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The authors consider the setting of metric learning. They prove bounds on the Radermacher complexity of embeddings-composed-with-distance-functions for a particular architecture of neural network, with different results for the 'dense' and 'sparse' regimes. \n", "main_review": "**Caveats:**\n-... |
zPLQSnfd14w | RMMuZkxCsrB | 2,022 | Two Regimes of Generalization for Non-Linear Metric Learning | A common approach to metric learning is to seek an embedding of the input data that behaves well with respect to the labels. While generalization bounds for linear embeddings are known, the non-linear case is not well understood. In this work we fill this gap by
providing uniform generalization guarantees for the cas... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper tries to provide uniform guarantees for the DNN type metric embeddings.", "main_review": "Strengths: \nIt is indeed a promising research direction to regard neural networks as a special nonlinear metric embedding.\n\nWeakness:\n1.\tThis paper only uses metric embedding to tell a sto... |
zPLQSnfd14w | bmXMP79ttn_ | 2,022 | Two Regimes of Generalization for Non-Linear Metric Learning | A common approach to metric learning is to seek an embedding of the input data that behaves well with respect to the labels. While generalization bounds for linear embeddings are known, the non-linear case is not well understood. In this work we fill this gap by
providing uniform generalization guarantees for the cas... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper provides two new generalization bounds for non-linear metric learning with deep neural networks, by extending results of Bartlett et al. 2017 to the metric learning setting. The two bounds have been called the 'sparse' and 'non-sparse' bounds and differ in the norm used for the last ... |
zNR43c03lRy | g1hhvDiMHVn | 2,022 | Learning to Annotate Part Segmentation with Gradient Matching | The success of state-of-the-art deep neural networks heavily relies on the presence of large-scale labelled datasets, which are extremely expensive and time-consuming to annotate. This paper focuses on tackling semi-supervised part segmentation tasks by generating high-quality images with a pre-trained GAN and labellin... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "In this paper, the authors mainly propose a gradient-matching-based method for part segmentation to reduce the annotation cost. Based on the DatasetGAN, the proposed model also used the Style GAN family to generate high-quality images and remove the human annotations on a handful of synthesize... |
zNR43c03lRy | K1hwLF4A5cS | 2,022 | Learning to Annotate Part Segmentation with Gradient Matching | The success of state-of-the-art deep neural networks heavily relies on the presence of large-scale labelled datasets, which are extremely expensive and time-consuming to annotate. This paper focuses on tackling semi-supervised part segmentation tasks by generating high-quality images with a pre-trained GAN and labellin... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This work deals with the problem of training a part segmentation network by automatically synthesizing pairs of images and annotations. The authors propose a training method of an annotator given the well-pretrained generator model. The formulation is well-motivated and converged to the gradie... |
zNR43c03lRy | HI5dVMRG868 | 2,022 | Learning to Annotate Part Segmentation with Gradient Matching | The success of state-of-the-art deep neural networks heavily relies on the presence of large-scale labelled datasets, which are extremely expensive and time-consuming to annotate. This paper focuses on tackling semi-supervised part segmentation tasks by generating high-quality images with a pre-trained GAN and labellin... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper proposes a method to solve the problem that generally requires large-scale labeled datasets to train deep learning models. The proposed method is designed to solve the nested-loop optimization problem (with an annotator that generates a label and a student network that predicts a la... |
zNR43c03lRy | _VXGf3EX4zm | 2,022 | Learning to Annotate Part Segmentation with Gradient Matching | The success of state-of-the-art deep neural networks heavily relies on the presence of large-scale labelled datasets, which are extremely expensive and time-consuming to annotate. This paper focuses on tackling semi-supervised part segmentation tasks by generating high-quality images with a pre-trained GAN and labellin... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The ultimate goal of the paper is to train an unsupervised generative model, in a semi-supervised manner, as a synthetic training example generator for training segmentation models. Prior works (eg. DatasetGAN) show that one can label a few synthetic images from a pre-trained generative model,... |
zNHzqZ9wrRB | Dwa3Jbqmshg | 2,022 | Equivariant Transformers for Neural Network based Molecular Potentials | The prediction of quantum mechanical properties is historically plagued by a trade-off between accuracy and speed. Machine learning potentials have previously shown great success in this domain, reaching increasingly better accuracy while maintaining computational efficiency comparable with classical force fields. In t... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper proposed equivariant transformers --- a neural network based algorithm to predict properties of molecules. The architecture is built upon the traditional transformer architecture, combined with some modifications specific to molecular property prediction tasks, such as exponential n... |
zNHzqZ9wrRB | TjdbneJCYa4 | 2,022 | Equivariant Transformers for Neural Network based Molecular Potentials | The prediction of quantum mechanical properties is historically plagued by a trade-off between accuracy and speed. Machine learning potentials have previously shown great success in this domain, reaching increasingly better accuracy while maintaining computational efficiency comparable with classical force fields. In t... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper describes an equivariant neural network (ET) with attention mechanisms that is applied to the prediction of molecular properties. The ET performs competitive with previous approaches on commonly used benchmark data.", "main_review": "The paper is well structured and the proposed meth... |
zNHzqZ9wrRB | UPawlAhAAYq | 2,022 | Equivariant Transformers for Neural Network based Molecular Potentials | The prediction of quantum mechanical properties is historically plagued by a trade-off between accuracy and speed. Machine learning potentials have previously shown great success in this domain, reaching increasingly better accuracy while maintaining computational efficiency comparable with classical force fields. In t... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The authors introduce a novel architecture for ML force fields, the Equivariant transformer (ET). It is based on the Transformer approach and can be used to predict energies (and forces) and other molecular properties (e.g., QM targets). The performance on standard benchmarks such as QM9 and M... |
zNHzqZ9wrRB | 18PH99BmXaW | 2,022 | Equivariant Transformers for Neural Network based Molecular Potentials | The prediction of quantum mechanical properties is historically plagued by a trade-off between accuracy and speed. Machine learning potentials have previously shown great success in this domain, reaching increasingly better accuracy while maintaining computational efficiency comparable with classical force fields. In t... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper presents an equivariant transformer model for predicting quantum mechanical properties from an atomic graph. The model obtains SOTA or near-SOTA results on three popular datasets while maintaining good computational efficiency. The primary novelty in their method is a new way to comp... |
zLb9oSWy933 | _uymrH5KAs6 | 2,022 | Fast Finite Width Neural Tangent Kernel | The Neural Tangent Kernel (NTK), defined as the outer product of the neural network (NN) Jacobians, $\Theta_\theta(x_1, x_2) = \left[\partial f(\theta, x_1)\big/\partial \theta\right] \left[\partial f(\theta, x_2)\big/\partial \theta\right]^T$, has emerged as a central object of study in deep learning. In the infinite ... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This work aims to solve the computation problem of the finite-width neural tangent kernel (NTK), which is a central object in deep learning. The authors analyze the computation and memory requirements for finite-width NTK and propose two novel algorithms that can improve efficiency. Open-sourc... |
zLb9oSWy933 | WPVoHUX2aO8 | 2,022 | Fast Finite Width Neural Tangent Kernel | The Neural Tangent Kernel (NTK), defined as the outer product of the neural network (NN) Jacobians, $\Theta_\theta(x_1, x_2) = \left[\partial f(\theta, x_1)\big/\partial \theta\right] \left[\partial f(\theta, x_2)\big/\partial \theta\right]^T$, has emerged as a central object of study in deep learning. In the infinite ... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "Experiments are convincing. The provided code is helpful for researchers who need a fast computation of NTK. Though the ideological (mathematical part) is very simple.", "main_review": "The paper describes three methods for computing the neural tangent kernel for a given a batch of vectors and... |
zLb9oSWy933 | FnWeeyLcfkv | 2,022 | Fast Finite Width Neural Tangent Kernel | The Neural Tangent Kernel (NTK), defined as the outer product of the neural network (NN) Jacobians, $\Theta_\theta(x_1, x_2) = \left[\partial f(\theta, x_1)\big/\partial \theta\right] \left[\partial f(\theta, x_2)\big/\partial \theta\right]^T$, has emerged as a central object of study in deep learning. In the infinite ... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper studies the practical compute and memory requirements to computing the Neural Tangent Kernel (NTK), introducing two new approaches to doing so for standard NN primitives (structured derivative and NTK-vector product) which each have advantages (in terms of variables like batch size,... |
zLb9oSWy933 | BYbuvXI-lDD | 2,022 | Fast Finite Width Neural Tangent Kernel | The Neural Tangent Kernel (NTK), defined as the outer product of the neural network (NN) Jacobians, $\Theta_\theta(x_1, x_2) = \left[\partial f(\theta, x_1)\big/\partial \theta\right] \left[\partial f(\theta, x_2)\big/\partial \theta\right]^T$, has emerged as a central object of study in deep learning. In the infinite ... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper studies an in-depth analysis of runtime and memory requirements for computing the finite-width NTK. The authors analyze computing costs of Jacobian-vector products (and vice versa) for both fully-connected and convolutional neural networks. They also improve the NTK computation cost... |
zKbMQ2NY1y | HElz5vYaGT | 2,022 | Aug-ILA: More Transferable Intermediate Level Attacks with Augmented References | An intriguing property of deep neural networks is that adversarial attacks can transfer across different models. Existing methods such as the Intermediate Level Attack (ILA) further improve black-box transferability by fine-tuning a reference adversarial attack, so as to maximize the perturbation on a pre-specified lay... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The authors proposed / used three techniques to enhance the transferability of ILA on undefended models. The techniques include image augmentation, reverse adversarial update on the clean example and reference attack update through interpolation with an automatic parameter selection scheme. Th... |
zKbMQ2NY1y | YPCMte9btvk | 2,022 | Aug-ILA: More Transferable Intermediate Level Attacks with Augmented References | An intriguing property of deep neural networks is that adversarial attacks can transfer across different models. Existing methods such as the Intermediate Level Attack (ILA) further improve black-box transferability by fine-tuning a reference adversarial attack, so as to maximize the perturbation on a pre-specified lay... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper presents a transfer-based attack method based on Intermediate Level Attack(ILA). Image augementation and reverse adversarial updateare applied to ILA input, to make diverse adversarial references. Moreover, the interpolation of cumlative attacks can maintain a better transfer direct... |
zKbMQ2NY1y | QZjkSfSxk81 | 2,022 | Aug-ILA: More Transferable Intermediate Level Attacks with Augmented References | An intriguing property of deep neural networks is that adversarial attacks can transfer across different models. Existing methods such as the Intermediate Level Attack (ILA) further improve black-box transferability by fine-tuning a reference adversarial attack, so as to maximize the perturbation on a pre-specified lay... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "This paper introduces improvements over Transferable Intermediate-level Attacks (ILA), by incorporating data augmentation into the attack tuning stage. The data augmentations introduced include 3 kinds: simple transformations (cropping), reverse-adversarial update, and attack interpolation. An... |
zKbMQ2NY1y | x5diiyntoan | 2,022 | Aug-ILA: More Transferable Intermediate Level Attacks with Augmented References | An intriguing property of deep neural networks is that adversarial attacks can transfer across different models. Existing methods such as the Intermediate Level Attack (ILA) further improve black-box transferability by fine-tuning a reference adversarial attack, so as to maximize the perturbation on a pre-specified lay... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The paper proposed the augmented Intermediate Level Attack (ILA) algorithm to strengthen the transferability of adversarial examples. Also, it claimed that increasing the diversity of input references could improve the generalization of adversarial examples when attacking different models. Spe... |
zIUyj55nXR | fdClrbLgAga | 2,022 | Frame Averaging for Invariant and Equivariant Network Design | Many machine learning tasks involve learning functions that are known to be invariant or equivariant to certain symmetries of the input data. However, it is often challenging to design neural network architectures that respect these symmetries while being expressive and computationally efficient. For example, Euclidean... | You are an expert academic peer reviewer for ICLR 2022.
Read the paper provided in the next message and write a complete review as a JSON object with the following fields:
- "summary_of_the_paper" (string): Provide a brief summary of the paper and its contributions.
- "main_review" (string): Please list both the stren... | {paper_markdown} | {"summary_of_the_paper": "The authors introduce Frame Averaging (FA), a general framework for adapting known architectures to become invariant or equivariant with respect to a general group by using group averaging operator. The idea of FA is to replace the averaging operator over the entire group by the averaging over... |
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