ICLR 2022

1,094 papers

Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL

Yanchao Sun, Ruijie Zheng, Yongyuan Liang, Furong Huang

Trigger Hunting with a Topological Prior for Trojan Detection

Xiaoling Hu, Xiao Lin, Michael Cogswell, Yi Yao, Susmit Jha

Convergent and Efficient Deep Q Learning Algorithm

Zhikang T. Wang, Masahito Ueda

A Theory of Tournament Representations

Arun Rajkumar, Vishnu Veerathu, Abdul Bakey Mir

Improving Non-Autoregressive Translation Models Without Distillation

Xiao Shi Huang, Felipe Perez, Maksims Volkovs

PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions

Zhaoqi Leng, Mingxing Tan, Chenxi Liu, Ekin Dogus Cubuk, Jay Shi

Generalisation in Lifelong Reinforcement Learning through Logical Composition

Geraud Nangue Tasse, Steven James, Benjamin Rosman

Understanding the Variance Collapse of SVGD in High Dimensions

Jimmy Ba, Murat A Erdogdu, Marzyeh Ghassemi, Shengyang Sun, Taiji Suzuki

Do Users Benefit From Interpretable Vision? A User Study, Baseline, And Dataset

Leon Sixt, Martin Schuessler, Oana-Iuliana Popescu, Philipp Weiß, Tim Landgraf

Gradient Importance Learning for Incomplete Observations

Qitong Gao, Dong Wang, Joshua David Amason, Siyang Yuan, Chenyang Tao

NETWORK INSENSITIVITY TO PARAMETER NOISE VIA PARAMETER ATTACK DURING TRAINING

Julian Büchel, Fynn Firouz Faber, Dylan Richard Muir

From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness

Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah

KL Guided Domain Adaptation

A. Tuan Nguyen, Toan Tran, Yarin Gal, Philip Torr, Atilim Gunes Baydin

Maximum n-times Coverage for Vaccine Design

Ge Liu, Alexander Dimitrakakis, Brandon Carter, David Gifford

Universalizing Weak Supervision

Changho Shin, Winfred Li, Harit Vishwakarma, Nicholas Carl Roberts, Frederic Sala

Bayesian Framework for Gradient Leakage

Mislav Balunovic, Dimitar Iliev Dimitrov, Robin Staab, Martin Vechev

AlphaZero-based Proof Cost Network to Aid Game Solving

Ti-Rong Wu, Chung-Chin Shih, Ting Han Wei, Meng-Yu Tsai, Wei-Yuan Hsu

A Neural Tangent Kernel Perspective of Infinite Tree Ensembles

Ryuichi Kanoh, Mahito Sugiyama

Heteroscedastic Temporal Variational Autoencoder For Irregularly Sampled Time Series

Satya Narayan Shukla, Benjamin Marlin

DISSECT: Disentangled Simultaneous Explanations via Concept Traversals

Asma Ghandeharioun, Been Kim, Chun-Liang Li, Brendan Jou, Brian Eoff

Scene Transformer: A unified architecture for predicting future trajectories of multiple agents

Jiquan Ngiam, Vijay Vasudevan, Benjamin Caine, Zhengdong Zhang, Hao-Tien Lewis Chiang

Contextualized Scene Imagination for Generative Commonsense Reasoning

Peifeng Wang, Jonathan Zamora, Junfeng Liu, Filip Ilievski, Muhao Chen

EigenGame Unloaded: When playing games is better than optimizing

Ian Gemp, Brian McWilliams, Claire Vernade, Thore Graepel

Fortuitous Forgetting in Connectionist Networks

Hattie Zhou, Ankit Vani, Hugo Larochelle, Aaron Courville

Optimal Representations for Covariate Shift

Yangjun Ruan, Yann Dubois, Chris J. Maddison

VC dimension of partially quantized neural networks in the overparametrized regime

Yutong Wang, Clayton Scott

Leveraging unlabeled data to predict out-of-distribution performance

Saurabh Garg, Sivaraman Balakrishnan, Zachary Chase Lipton, Behnam Neyshabur, Hanie Sedghi

On Distributed Adaptive Optimization with Gradient Compression

Xiaoyun Li, Belhal Karimi, Ping Li

Minimax Optimization with Smooth Algorithmic Adversaries

Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J Ratliff

A Program to Build E(N)-Equivariant Steerable CNNs

Gabriele Cesa, Leon Lang, Maurice Weiler

A Comparison of Hamming Errors of Representative Variable Selection Methods

Tracy Ke, Longlin Wang

ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods

victor schmidt, Alexandra Luccioni, Mélisande Teng, Tianyu Zhang, Alexia Reynaud

Exposing the Implicit Energy Networks behind Masked Language Models via Metropolis--Hastings

Kartik Goyal, Chris Dyer, Taylor Berg-Kirkpatrick

Towards General Function Approximation in Zero-Sum Markov Games

Baihe Huang, Jason D. Lee, Zhaoran Wang, Zhuoran Yang

DIVA: Dataset Derivative of a Learning Task

Yonatan Dukler, Alessandro Achille, Giovanni Paolini, Avinash Ravichandran, Marzia Polito

Graph Condensation for Graph Neural Networks

Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang

Selective Ensembles for Consistent Predictions

Emily Black, Klas Leino, Matt Fredrikson

On Evaluation Metrics for Graph Generative Models

Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham W. Taylor

Mind the Gap: Domain Gap Control for Single Shot Domain Adaptation for Generative Adversarial Networks

Peihao Zhu, Rameen Abdal, John Femiani, Peter Wonka

Benchmarking the Spectrum of Agent Capabilities

Danijar Hafner

Learning to Map for Active Semantic Goal Navigation

Georgios Georgakis, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Kostas Daniilidis

Audio Lottery: Speech Recognition Made Ultra-Lightweight, Noise-Robust, and Transferable

Shaojin Ding, Tianlong Chen, Zhangyang Wang

Capturing Structural Locality in Non-parametric Language Models

Frank F. Xu, Junxian He, Graham Neubig, Vincent Josua Hellendoorn

Distribution Compression in Near-Linear Time

Abhishek Shetty, Raaz Dwivedi, Lester Mackey

Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality

Daniel Watson, William Chan, Jonathan Ho, Mohammad Norouzi

Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound

Claudio Ferrari, Mark Niklas Mueller, Nikola Jovanović, Martin Vechev

AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation

David Berthelot, Rebecca Roelofs, Kihyuk Sohn, Nicholas Carlini, Alexey Kurakin

Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?

Yonggan Fu, Shunyao Zhang, Shang Wu, Cheng Wan, Yingyan Lin

Learning Towards The Largest Margins

Xiong Zhou, Xianming Liu, Deming Zhai, Junjun Jiang, Xin Gao

Neural Network Approximation based on Hausdorff distance of Tropical Zonotopes

Panagiotis Misiakos, Georgios Smyrnis, George Retsinas, Petros Maragos

DeSKO: Stability-Assured Robust Control with a Deep Stochastic Koopman Operator

Minghao Han, Jacob Euler-Rolle, Robert K. Katzschmann

NeuPL: Neural Population Learning

Siqi Liu, Luke Marris, Daniel Hennes, Josh Merel, Nicolas Heess

Interacting Contour Stochastic Gradient Langevin Dynamics

Wei Deng, SIQI LIANG, Botao Hao, Guang Lin, Faming Liang

Can an Image Classifier Suffice For Action Recognition?

Quanfu Fan, Chun-Fu Chen, Rameswar Panda

Non-Parallel Text Style Transfer with Self-Parallel Supervision

Ruibo Liu, Chongyang Gao, Chenyan Jia, Guangxuan Xu, Soroush Vosoughi

Optimization and Adaptive Generalization of Three layer Neural Networks

Khashayar Gatmiry, Stefanie Jegelka, Jonathan Kelner

Understanding and Leveraging Overparameterization in Recursive Value Estimation

Chenjun Xiao, Bo Dai, Jincheng Mei, Oscar A Ramirez, Ramki Gummadi

Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations

Anuroop Sriram, Abhishek Das, Brandon M Wood, Siddharth Goyal, C. Lawrence Zitnick

Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators

Yu Meng, Chenyan Xiong, Payal Bajaj, saurabh tiwary, Paul N. Bennett

On the Convergence of Certified Robust Training with Interval Bound Propagation

Yihan Wang, Zhouxing Shi, Quanquan Gu, Cho-jui Hsieh

Neural Link Prediction with Walk Pooling

Liming Pan, Cheng Shi, Ivan Dokmanić

CROP: Certifying Robust Policies for Reinforcement Learning through Functional Smoothing

Fan Wu, Linyi Li, Zijian Huang, Yevgeniy Vorobeychik, Ding Zhao

It Takes Four to Tango: Multiagent Self Play for Automatic Curriculum Generation

Yuqing Du, Pieter Abbeel, Aditya Grover

Discriminative Similarity for Data Clustering

Yingzhen Yang, Ping Li

PI3NN: Out-of-distribution-aware Prediction Intervals from Three Neural Networks

Siyan Liu, Pei Zhang, Dan Lu, Guannan Zhang

Neural Contextual Bandits with Deep Representation and Shallow Exploration

Pan Xu, Zheng Wen, Handong Zhao, Quanquan Gu

MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining

Ahmed Imtiaz Humayun, Randall Balestriero, Richard Baraniuk

Evaluating Distributional Distortion in Neural Language Modeling

Benjamin LeBrun, Alessandro Sordoni, Timothy J. O'Donnell

Divisive Feature Normalization Improves Image Recognition Performance in AlexNet

Michelle Miller, SueYeon Chung, Kenneth D. Miller

PEARL: Data Synthesis via Private Embeddings and Adversarial Reconstruction Learning

Seng Pei Liew, Tsubasa Takahashi, Michihiko Ueno

CrossBeam: Learning to Search in Bottom-Up Program Synthesis

Kensen Shi, Hanjun Dai, Kevin Ellis, Charles Sutton

Fast Regression for Structured Inputs

Raphael A Meyer, Cameron N Musco, Christopher P Musco, David Woodruff, Samson Zhou

Value Function Spaces: Skill-Centric State Abstractions for Long-Horizon Reasoning

Dhruv Shah, Peng Xu, Yao Lu, Ted Xiao, Alexander T Toshev

Approximation and Learning with Deep Convolutional Models: a Kernel Perspective

Alberto Bietti

Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future

Harshavardhan Kamarthi, Alexander Rodriguez, B. Aditya Prakash

Anisotropic Random Feature Regression in High Dimensions

Gabriel Mel, Jeffrey Pennington

Top-label calibration and multiclass-to-binary reductions

Chirag Gupta, Aaditya Ramdas

Resonance in Weight Space: Covariate Shift Can Drive Divergence of SGD with Momentum

Kirby Banman, Garnet Liam Peet-Pare, Nidhi Hegde, Alona Fyshe, Martha White

AEVA: Black-box Backdoor Detection Using Adversarial Extreme Value Analysis

Junfeng Guo, Ang Li, Cong Liu

Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations

Aahlad Manas Puli, Lily H Zhang, Eric Karl Oermann, Rajesh Ranganath

Sound Adversarial Audio-Visual Navigation

Yinfeng Yu, Wenbing Huang, Fuchun Sun, Changan Chen, Yikai Wang

Sample and Computation Redistribution for Efficient Face Detection

Jia Guo, Jiankang Deng, Alexandros Lattas, Stefanos Zafeiriou

Variational Predictive Routing with Nested Subjective Timescales

Alexey Zakharov, Qinghai Guo, Zafeirios Fountas

From Intervention to Domain Transportation: A Novel Perspective to Optimize Recommendation

Da Xu, Yuting Ye, Chuanwei Ruan, Evren Korpeoglu, Sushant Kumar

Diverse Client Selection for Federated Learning via Submodular Maximization

Ravikumar Balakrishnan, Tian Li, Tianyi Zhou, Nageen Himayat, Virginia Smith

Sequence Approximation using Feedforward Spiking Neural Network for Spatiotemporal Learning: Theory and Optimization Methods

Xueyuan She, Saurabh Dash, Saibal Mukhopadhyay

Improving Mutual Information Estimation with Annealed and Energy-Based Bounds

Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger Baker Grosse

DEGREE: Decomposition Based Explanation for Graph Neural Networks

Qizhang Feng, Ninghao Liu, Fan Yang, Ruixiang Tang, Mengnan Du

Is Homophily a Necessity for Graph Neural Networks?

Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang

Recycling Model Updates in Federated Learning: Are Gradient Subspaces Low-Rank?

Sheikh Shams Azam, Seyyedali Hosseinalipour, Qiang Qiu, Christopher Brinton

L0-Sparse Canonical Correlation Analysis

Ofir Lindenbaum, Moshe Salhov, Amir Averbuch, Yuval Kluger

Wish you were here: Hindsight Goal Selection for long-horizon dexterous manipulation

Todor Davchev, Oleg Olegovich Sushkov, Jean-Baptiste Regli, Stefan Schaal, Yusuf Aytar

Variational Neural Cellular Automata

Rasmus Berg Palm, Miguel González Duque, Shyam Sudhakaran, Sebastian Risi

Learning to Downsample for Segmentation of Ultra-High Resolution Images

Chen Jin, Ryutaro Tanno, Thomy Mertzanidou, Eleftheria Panagiotaki, Daniel C. Alexander