ICLR 2021

859 papers

MIROSTAT: A NEURAL TEXT DECODING ALGORITHM THAT DIRECTLY CONTROLS PERPLEXITY

Sourya Basu, Govardana Sachitanandam Ramachandran, Nitish Shirish Keskar, Lav R. Varshney

C-Learning: Horizon-Aware Cumulative Accessibility Estimation

Panteha Naderian, Gabriel Loaiza-Ganem, Harry J. Braviner, Anthony L. Caterini, Jesse C. Cresswell

A Hypergradient Approach to Robust Regression without Correspondence

Yujia Xie, Yixiu Mao, Simiao Zuo, Hongteng Xu, Xiaojing Ye

Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes

Jake Snell, Richard Zemel

INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving

Yuhuai Wu, Albert Jiang, Jimmy Ba, Roger Baker Grosse

HalentNet: Multimodal Trajectory Forecasting with Hallucinative Intents

Deyao Zhu, Mohamed Zahran, Li Erran Li, Mohamed Elhoseiny

Deep Partition Aggregation: Provable Defenses against General Poisoning Attacks

Alexander Levine, Soheil Feizi

Filtered Inner Product Projection for Crosslingual Embedding Alignment

Vin Sachidananda, Ziyi Yang, Chenguang Zhu

Understanding Over-parameterization in Generative Adversarial Networks

Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger

Decoupling Global and Local Representations via Invertible Generative Flows

Xuezhe Ma, Xiang Kong, Shanghang Zhang, Eduard H Hovy

Distance-Based Regularisation of Deep Networks for Fine-Tuning

Henry Gouk, Timothy Hospedales, Massimiliano Pontil

Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU

Patrick Kidger, Terry Lyons

Scalable Transfer Learning with Expert Models

Joan Puigcerver, Carlos Riquelme Ruiz, Basil Mustafa, Cedric Renggli, André Susano Pinto

Faster Binary Embeddings for Preserving Euclidean Distances

Jinjie Zhang, Rayan Saab

Implicit Gradient Regularization

David Barrett, Benoit Dherin

Estimating Lipschitz constants of monotone deep equilibrium models

Chirag Pabbaraju, Ezra Winston, J Zico Kolter

Molecule Optimization by Explainable Evolution

Binghong Chen, Tianzhe Wang, Chengtao Li, Hanjun Dai, Le Song

Negative Data Augmentation

Abhishek Sinha, Kumar Ayush, Jiaming Song, Burak Uzkent, Hongxia Jin

NOVAS: Non-convex Optimization via Adaptive Stochastic Search for End-to-end Learning and Control

Ioannis Exarchos, Marcus Aloysius Pereira, Ziyi Wang, Evangelos Theodorou

Shape or Texture: Understanding Discriminative Features in CNNs

Md Amirul Islam, Matthew Kowal, Patrick Esser, Sen Jia, Bjorn Ommer

Reinforcement Learning with Random Delays

Yann Bouteiller, Simon Ramstedt, Giovanni Beltrame, Christopher Pal, Jonathan Binas

Shapley explainability on the data manifold

Christopher Frye, Damien de Mijolla, Tom Begley, Laurence Cowton, Megan Stanley

Adaptive Extra-Gradient Methods for Min-Max Optimization and Games

Kimon Antonakopoulos, Veronica Belmega, Panayotis Mertikopoulos

Usable Information and Evolution of Optimal Representations During Training

Michael Kleinman, Alessandro Achille, Daksh Idnani, Jonathan Kao

Understanding the failure modes of out-of-distribution generalization

Vaishnavh Nagarajan, Anders Andreassen, Behnam Neyshabur

Projected Latent Markov Chain Monte Carlo: Conditional Sampling of Normalizing Flows

Chris Cannella, Mohammadreza Soltani, Vahid Tarokh

Towards Robust Neural Networks via Close-loop Control

Zhuotong Chen, Qianxiao Li, Zheng Zhang

The geometry of integration in text classification RNNs

Kyle Aitken, Vinay Venkatesh Ramasesh, Ankush Garg, Yuan Cao, David Sussillo

On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning

REN WANG, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng

Anatomy of Catastrophic Forgetting: Hidden Representations and Task Semantics

Vinay Venkatesh Ramasesh, Ethan Dyer, Maithra Raghu

Simple Spectral Graph Convolution

Hao Zhu, Piotr Koniusz

Neural Networks for Learning Counterfactual G-Invariances from Single Environments

S Chandra Mouli, Bruno Ribeiro

LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition

Valeriia Cherepanova, Micah Goldblum, Harrison Foley, Shiyuan Duan, John P Dickerson

Provable Rich Observation Reinforcement Learning with Combinatorial Latent States

Dipendra Misra, Qinghua Liu, Chi Jin, John Langford

Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments

Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Charles Blundell

IsarStep: a Benchmark for High-level Mathematical Reasoning

Wenda Li, Lei Yu, Yuhuai Wu, Lawrence C. Paulson

Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction

Wei Deng, Qi Feng, Georgios P. Karagiannis, Guang Lin, Faming Liang

Fantastic Four: Differentiable and Efficient Bounds on Singular Values of Convolution Layers

Sahil Singla, Soheil Feizi

Beyond Categorical Label Representations for Image Classification

Boyuan Chen, Yu Li, Sunand Raghupathi, Hod Lipson

Improved Estimation of Concentration Under ℓ_p-Norm Distance Metrics Using Half Spaces

Jack Prescott, Xiao Zhang, David Evans

Cross-Attentional Audio-Visual Fusion for Weakly-Supervised Action Localization

Jun-Tae Lee, Mihir Jain, Hyoungwoo Park, Sungrack Yun

Learning Structural Edits via Incremental Tree Transformations

Ziyu Yao, Frank F. Xu, Pengcheng Yin, Huan Sun, Graham Neubig

Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification

Francisco Utrera, Evan Kravitz, N. Benjamin Erichson, Rajiv Khanna, Michael W. Mahoney

Return-Based Contrastive Representation Learning for Reinforcement Learning

Guoqing Liu, Chuheng Zhang, Li Zhao, Tao Qin, Jinhua Zhu

Provably robust classification of adversarial examples with detection

Fatemeh Sheikholeslami, Ali Lotfi, J Zico Kolter

Control-Aware Representations for Model-based Reinforcement Learning

Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh

Chaos of Learning Beyond Zero-sum and Coordination via Game Decompositions

Yun Kuen Cheung, Yixin Tao

Learning Long-term Visual Dynamics with Region Proposal Interaction Networks

Haozhi Qi, Xiaolong Wang, Deepak Pathak, Yi Ma, Jitendra Malik

Combining Label Propagation and Simple Models out-performs Graph Neural Networks

Qian Huang, Horace He, Abhay Singh, Ser-Nam Lim, Austin Benson

Pre-training Text-to-Text Transformers for Concept-centric Common Sense

Wangchunshu Zhou, Dong-Ho Lee, Ravi Kiran Selvam, Seyeon Lee, Xiang Ren

Benchmarks for Deep Off-Policy Evaluation

Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang

Contrastive Syn-to-Real Generalization

Wuyang Chen, Zhiding Yu, Shalini De Mello, Sifei Liu, Jose M. Alvarez

Early Stopping in Deep Networks: Double Descent and How to Eliminate it

Reinhard Heckel, Fatih Furkan Yilmaz

Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning

Beliz Gunel, Jingfei Du, Alexis CONNEAU, Veselin Stoyanov

Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth

Thao Nguyen, Maithra Raghu, Simon Kornblith

Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding

Sana Tonekaboni, Danny Eytan, Anna Goldenberg

Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective

Wuyang Chen, Xinyu Gong, Zhangyang Wang

PolarNet: Learning to Optimize Polar Keypoints for Keypoint Based Object Detection

Wu Xiongwei, Doyen Sahoo, Steven Hoi

Representing Partial Programs with Blended Abstract Semantics

Maxwell Nye, Yewen Pu, Matthew Bowers, Jacob Andreas, Joshua B. Tenenbaum

CompOFA – Compound Once-For-All Networks for Faster Multi-Platform Deployment

Manas Sahni, Shreya Varshini, Alind Khare, Alexey Tumanov

Discovering Non-monotonic Autoregressive Orderings with Variational Inference

Xuanlin Li, Brandon Trabucco, Dong Huk Park, Michael Luo, Sheng Shen

Are wider nets better given the same number of parameters?

Anna Golubeva, Guy Gur-Ari, Behnam Neyshabur

SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization

A F M Shahab Uddin, Mst. Sirazam Monira, Wheemyung Shin, TaeChoong Chung, Sung-Ho Bae

Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning

Xuebo Liu, Longyue Wang, Derek F. Wong, Liang Ding, Lidia S. Chao

Layer-adaptive Sparsity for the Magnitude-based Pruning

Jaeho Lee, Sejun Park, Sangwoo Mo, Sungsoo Ahn, Jinwoo Shin

Understanding and Improving Lexical Choice in Non-Autoregressive Translation

Liang Ding, Longyue Wang, Xuebo Liu, Derek F. Wong, Dacheng Tao

Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics

Yanchao Sun, Da Huo, Furong Huang

Meta-Learning with Neural Tangent Kernels

Yufan Zhou, Zhenyi Wang, Jiayi Xian, Changyou Chen, Jinhui Xu

Knowledge Distillation as Semiparametric Inference

Tri Dao, Govinda M Kamath, Vasilis Syrgkanis, Lester Mackey

Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation

Mrigank Raman, Aaron Chan, Siddhant Agarwal, Peifeng Wang, Hansen Wang

Deep Learning meets Projective Clustering

Alaa Maalouf, Harry Lang, Daniela Rus, Dan Feldman

CoDA: Contrast-enhanced and Diversity-promoting Data Augmentation for Natural Language Understanding

Yanru Qu, Dinghan Shen, Yelong Shen, Sandra Sajeev, Weizhu Chen

Cut out the annotator, keep the cutout: better segmentation with weak supervision

Sarah Hooper, Michael Wornow, Ying Hang Seah, Peter Kellman, hui xue

Into the Wild with AudioScope: Unsupervised Audio-Visual Separation of On-Screen Sounds

Efthymios Tzinis, Scott Wisdom, Aren Jansen, Shawn Hershey, Tal Remez

In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning

Mamshad Nayeem Rizve, Kevin Duarte, Yogesh S Rawat, Mubarak Shah

Teaching with Commentaries

Aniruddh Raghu, Maithra Raghu, Simon Kornblith, David Duvenaud, Geoffrey Hinton

Extreme Memorization via Scale of Initialization

Harsh Mehta, Ashok Cutkosky, Behnam Neyshabur

Learning Reasoning Paths over Semantic Graphs for Video-grounded Dialogues

Hung Le, Nancy F. Chen, Steven Hoi

Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein

Khai Nguyen, Son Nguyen, nhật Hồ, Tung Pham, Hung Bui

GANs Can Play Lottery Tickets Too

Xuxi Chen, Zhenyu Zhang, Yongduo Sui, Tianlong Chen

Adaptive Federated Optimization

Sashank J. Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush

Individually Fair Rankings

Amanda Bower, Hamid Eftekhari, Mikhail Yurochkin, Yuekai Sun

Decentralized Attribution of Generative Models

Changhoon Kim, Yi Ren, Yezhou Yang

Generative Scene Graph Networks

Fei Deng, Zhuo Zhi, Donghun Lee, Sungjin Ahn

gradSim: Differentiable simulation for system identification and visuomotor control

J. Krishna Murthy, Miles Macklin, Florian Golemo, Vikram Voleti, Linda Petrini

Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning

Zhenfang Chen, Jiayuan Mao, Jiajun Wu, Kwan-Yee Kenneth Wong, Joshua B. Tenenbaum

Property Controllable Variational Autoencoder via Invertible Mutual Dependence

Xiaojie Guo, Yuanqi Du, Liang Zhao

Learning Task Decomposition with Ordered Memory Policy Network

Yuchen Lu, Yikang Shen, Siyuan Zhou, Aaron Courville, Joshua B. Tenenbaum

Local Search Algorithms for Rank-Constrained Convex Optimization

Kyriakos Axiotis, Maxim Sviridenko

Robust Overfitting may be mitigated by properly learned smoothening

Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, Zhangyang Wang

Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks

Yanbang Wang, Yen-Yu Chang, Yunyu Liu, Jure Leskovec, Pan Li

ECONOMIC HYPERPARAMETER OPTIMIZATION WITH BLENDED SEARCH STRATEGY

Chi Wang, Qingyun Wu, Silu Huang, Amin Saied

SSD: A Unified Framework for Self-Supervised Outlier Detection

Vikash Sehwag, Mung Chiang, Prateek Mittal

Emergent Road Rules In Multi-Agent Driving Environments

Avik Pal, Jonah Philion, Yuan-Hong Liao, Sanja Fidler

Semi-supervised Keypoint Localization

Olga Moskvyak, Frederic Maire, Feras Dayoub, Mahsa Baktashmotlagh

Planning from Pixels using Inverse Dynamics Models

Keiran Paster, Sheila A. McIlraith, Jimmy Ba

Multiplicative Filter Networks

Rizal Fathony, Anit Kumar Sahu, Devin Willmott, J Zico Kolter

CaPC Learning: Confidential and Private Collaborative Learning

Christopher A. Choquette-Choo, Natalie Dullerud, Adam Dziedzic, Yunxiang Zhang, Somesh Jha

MixKD: Towards Efficient Distillation of Large-scale Language Models

Kevin J Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen

Efficient Empowerment Estimation for Unsupervised Stabilization

Ruihan Zhao, Kevin Lu, Pieter Abbeel, Stas Tiomkin