NeurIPS 2021

2,334 papers

Multiclass Boosting and the Cost of Weak Learning

Nataly Brukhim, Elad Hazan, Shay Moran, Indraneel Mukherjee, Robert E. Schapire

Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection

Chunjong Park, Anas Awadalla, Tadayoshi Kohno, Shwetak Patel

Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning

Jongjin Park, Younggyo Seo, Chang Liu, Li Zhao, Tao Qin

Visual Adversarial Imitation Learning using Variational Models

Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn

Misspecified Gaussian Process Bandit Optimization

Ilija Bogunovic, Andreas Krause

Convex-Concave Min-Max Stackelberg Games

Denizalp Goktas, Amy Greenwald

On the Existence of The Adversarial Bayes Classifier

Pranjal Awasthi, Natalie Frank, Mehryar Mohri

G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators

Yunhui Long, Boxin Wang, Zhuolin Yang, Bhavya Kailkhura, Aston Zhang

Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity

Kaiqing Zhang, Xiangyuan Zhang, Bin Hu, Tamer Basar

Dual Progressive Prototype Network for Generalized Zero-Shot Learning

Chaoqun Wang, Shaobo Min, Xuejin Chen, Xiaoyan Sun, Houqiang Li

Estimating the Long-Term Effects of Novel Treatments

Keith Battocchi, Eleanor Dillon, Maggie Hei, Greg Lewis, Miruna Oprescu

UCB-based Algorithms for Multinomial Logistic Regression Bandits

Sanae Amani, CHRISTOS THRAMPOULIDIS

Accumulative Poisoning Attacks on Real-time Data

Tianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su, Jun Zhu

Low-Rank Constraints for Fast Inference in Structured Models

Justin Chiu, Yuntian Deng, Alexander Rush

Iteratively Reweighted Least Squares for Basis Pursuit with Global Linear Convergence Rate

Christian Kümmerle, Claudio Mayrink Verdun, Dominik Stöger

Word2Fun: Modelling Words as Functions for Diachronic Word Representation

Benyou Wang, Emanuele Di Buccio, Massimo Melucci

Confident Anchor-Induced Multi-Source Free Domain Adaptation

Jiahua Dong, Zhen Fang, Anjin Liu, Gan Sun, Tongliang Liu

Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update

Michal Derezinski, Jonathan Lacotte, Mert Pilanci, Michael W. Mahoney

Distributed Principal Component Analysis with Limited Communication

Foivos Alimisis, Peter Davies, Bart Vandereycken, Dan Alistarh

MetaAvatar: Learning Animatable Clothed Human Models from Few Depth Images

Shaofei Wang, Marko Mihajlovic, Qianli Ma, Andreas Geiger, Siyu Tang

Smooth Normalizing Flows

Jonas Köhler, Andreas Krämer, Frank Noe

Goal-Aware Cross-Entropy for Multi-Target Reinforcement Learning

Kibeom Kim, Min Whoo Lee, Yoonsung Kim, JeHwan Ryu, Minsu Lee

Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis

Jikai Jin, Bohang Zhang, Haiyang Wang, Liwei Wang

Lip to Speech Synthesis with Visual Context Attentional GAN

Minsu Kim, Joanna Hong, Yong Man Ro

On Component Interactions in Two-Stage Recommender Systems

Jiri Hron, Karl Krauth, Michael I. Jordan, Niki Kilbertus

Online Knapsack with Frequency Predictions

Sungjin Im, Ravi Kumar, Mahshid Montazer Qaem, Manish Purohit

Constrained Robust Submodular Partitioning

Shengjie Wang, Tianyi Zhou, Chandrashekhar Lavania, Jeff A. Bilmes, Jeff A Bilmes

Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks

SHUAI ZHANG, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong

Aligned Structured Sparsity Learning for Efficient Image Super-Resolution

Yulun Zhang, Huan Wang, Can Qin, Yun Fu

Cardinality-Regularized Hawkes-Granger Model

Tsuyoshi Ide, Georgios Kollias, Dzung Phan, Naoki Abe

Pay Better Attention to Attention: Head Selection in Multilingual and Multi-Domain Sequence Modeling

Hongyu Gong, Yun Tang, Juan Pino, Xian Li

Hybrid Regret Bounds for Combinatorial Semi-Bandits and Adversarial Linear Bandits

Shinji Ito

Learning Conjoint Attentions for Graph Neural Nets

Tiantian He, Yew Soon Ong, L Bai

Weisfeiler and Lehman Go Cellular: CW Networks

Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yuguang Wang, Pietro Lió

Bias Out-of-the-Box: An Empirical Analysis of Intersectional Occupational Biases in Popular Generative Language Models

Hannah Rose Kirk, Yennie Jun, Filippo Volpin, Haider Iqbal, Elias Benussi

Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN

Zhenyu Xie, Zaiyu Huang, Fuwei Zhao, Haoye Dong, Michael Kampffmeyer

Test-Time Personalization with a Transformer for Human Pose Estimation

Yizhuo Li, Miao Hao, Zonglin Di, Nitesh Bharadwaj Gundavarapu, Xiaolong Wang

Explicit loss asymptotics in the gradient descent training of neural networks

Maksim Velikanov, Dmitry Yarotsky

Learning to See by Looking at Noise

Manel Baradad Jurjo, Jonas Wulff, Tongzhou Wang, Phillip Isola, Antonio Torralba

ReSSL: Relational Self-Supervised Learning with Weak Augmentation

Mingkai Zheng, Shan You, Fei Wang, Chen Qian, Changshui Zhang

On Model Calibration for Long-Tailed Object Detection and Instance Segmentation

Tai-Yu Pan, Cheng Zhang, Yandong Li, Hexiang Hu, Dong Xuan

Zero Time Waste: Recycling Predictions in Early Exit Neural Networks

Maciej Wołczyk, Bartosz Wójcik, Klaudia Bałazy, Igor T Podolak, Jacek Tabor

Automatic Symmetry Discovery with Lie Algebra Convolutional Network

Nima Dehmamy, Robin Walters, Yanchen Liu, Dashun Wang, Rose Yu

Associating Objects with Transformers for Video Object Segmentation

Zongxin Yang, Yunchao Wei, Yi Yang

A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics

Kai Xu, Akash Srivastava, Dan Gutfreund, Felix Sosa, Tomer Ullman

Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL

Charles Packer, Pieter Abbeel, Joseph E Gonzalez

Iterative Causal Discovery in the Possible Presence of Latent Confounders and Selection Bias

Raanan Y. Rohekar, Shami Nisimov, Yaniv Gurwicz, Gal Novik

Luna: Linear Unified Nested Attention

Xuezhe Ma, Xiang Kong, Sinong Wang, Chunting Zhou, Jonathan May

Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization

Yusuke Iwasawa, Yutaka Matsuo

Voxel-based 3D Detection and Reconstruction of Multiple Objects from a Single Image

Feng Liu, Xiaoming Liu

Understanding Instance-based Interpretability of Variational Auto-Encoders

Zhifeng Kong, Kamalika Chaudhuri

Preserved central model for faster bidirectional compression in distributed settings

Constantin Philippenko, Aymeric Dieuleveut

Solving Min-Max Optimization with Hidden Structure via Gradient Descent Ascent

Emmanouil-Vasileios Vlatakis-Gkaragkounis, Lampros Flokas, Georgios Piliouras

Self-Interpretable Model with Transformation Equivariant Interpretation

Yipei Wang, Xiaoqian Wang

Memory-efficient Patch-based Inference for Tiny Deep Learning

Ji Lin, Wei-Ming Chen, Han Cai, Chuang Gan, Song Han

Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time

Feng Zhu, Andrew Sedler, Harrison A Grier, Nauman Ahad, Mark Davenport

Continuous-time edge modelling using non-parametric point processes

Xuhui Fan, Bin Li, Feng Zhou, Scott SIsson

Representation Learning on Spatial Networks

Zheng Zhang, Liang Zhao

Robustifying Algorithms of Learning Latent Trees with Vector Variables

Fengzhuo Zhang, Vincent Tan

Explaining Hyperparameter Optimization via Partial Dependence Plots

Julia Moosbauer, Julia Herbinger, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl

A Gang of Adversarial Bandits

Mark Herbster, Stephen Pasteris, Fabio Vitale, Massimiliano Pontil

Reinforcement Learning in Reward-Mixing MDPs

Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

Circa: Stochastic ReLUs for Private Deep Learning

Zahra Ghodsi, Nandan Kumar Jha, Brandon Reagen, Siddharth Garg

On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method

Junyu Zhang, Chengzhuo Ni, zheng Yu, Csaba Szepesvári, Mengdi Wang

On Calibration and Out-of-Domain Generalization

Yoav Wald, Amir Feder, Daniel Greenfeld, Uri Shalit

Evolution Gym: A Large-Scale Benchmark for Evolving Soft Robots

Jagdeep Bhatia, Holly Jackson, Yunsheng Tian, Jie Xu, Wojciech Matusik

Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement

Samuel Daulton, Maximilian Balandat, Eytan Bakshy

Generalization Bounds for Meta-Learning via PAC-Bayes and Uniform Stability

Alec Farid, Anirudha Majumdar

Inverse-Weighted Survival Games

Xintian Han, Mark Goldstein, Aahlad Puli, Thomas Wies, Adler J. Perotte

Multi-view Contrastive Graph Clustering

ErLin Pan, Zhao Kang

TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification

Zhuchen Shao, Hao Bian, Yang Chen, Yifeng Wang, Jian Zhang

Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr\"om Method

Yifan Chen, Qi Zeng, Heng Ji, Yun Yang

Discrete-Valued Neural Communication

Dianbo Liu, Alex M Lamb, Kenji Kawaguchi, Anirudh Goyal ALIAS PARTH GOYAL, Chen Sun

Optimal Rates for Random Order Online Optimization

Uri Sherman, Tomer Koren, Yishay Mansour

Adversarial Attacks on Black Box Video Classifiers: Leveraging the Power of Geometric Transformations

Shasha Li, Abhishek Aich, Shitong Zhu, Salman Asif, Chengyu Song

Minimizing Polarization and Disagreement in Social Networks via Link Recommendation

Liwang Zhu, Qi Bao, Zhongzhi Zhang

Improving Conditional Coverage via Orthogonal Quantile Regression

Shai Feldman, Stephen Bates, Yaniv Romano

Do Input Gradients Highlight Discriminative Features?

Harshay Shah, Prateek Jain, Praneeth Netrapalli

INDIGO: GNN-Based Inductive Knowledge Graph Completion Using Pair-Wise Encoding

Shuwen Liu, Bernardo Grau, Ian Horrocks, Egor Kostylev

Is Automated Topic Model Evaluation Broken? The Incoherence of Coherence

Alexander Hoyle, Pranav Goel, Andrew Hian-Cheong, Denis Peskov, Jordan Boyd-Graber

Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs

harsh satija, Philip S. Thomas, Joelle Pineau, Romain Laroche

TransMatcher: Deep Image Matching Through Transformers for Generalizable Person Re-identification

Shengcai Liao, Ling Shao

Temporally Abstract Partial Models

Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, Doina Precup

Breaking the Dilemma of Medical Image-to-image Translation

Lingke Kong, Chenyu Lian, Detian Huang, zhenjiang li, Yanle Hu

Efficient Truncated Linear Regression with Unknown Noise Variance

Constantinos Daskalakis, Patroklos Stefanou, Rui Yao, Emmanouil Zampetakis

Online Multi-Armed Bandits with Adaptive Inference

Maria Dimakopoulou, Zhimei Ren, Zhengyuan Zhou

Self-Diagnosing GAN: Diagnosing Underrepresented Samples in Generative Adversarial Networks

Jinhee Lee, Haeri Kim, Youngkyu Hong, Hye Won Chung

Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics

Ingmar Schubert, Danny Driess, Ozgur S. Oguz, Marc Toussaint

There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning

Nathan Grinsztajn, Johan Ferret, Olivier Pietquin, Philippe Preux, Matthieu Geist

Replay-Guided Adversarial Environment Design

Minqi Jiang, Michael Dennis, Jack Parker-Holder, Jakob Foerster, Edward Grefenstette

Wisdom of the Crowd Voting: Truthful Aggregation of Voter Information and Preferences

Grant Schoenebeck, Biaoshuai Tao

Shift Invariance Can Reduce Adversarial Robustness

Vasu Singla, Songwei Ge, Basri Ronen, David Jacobs

End-to-End Weak Supervision

Salva Rühling Cachay, Benedikt Boecking, Artur Dubrawski

Reliable Decisions with Threshold Calibration

Roshni Sahoo, Shengjia Zhao, Alyssa Chen, Stefano Ermon

NxMTransformer: Semi-Structured Sparsification for Natural Language Understanding via ADMM

Connor Holmes, Minjia Zhang, Yuxiong He, Bo Wu

Early-stopped neural networks are consistent

Ziwei Ji, Justin Li, Matus J. Telgarsky

Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization

Haochuan Li, Yi Tian, Jingzhao Zhang, Ali Jadbabaie

You are caught stealing my winning lottery ticket! Making a lottery ticket claim its ownership

Xuxi Chen, Tianlong Chen, Zhenyu Zhang, Zhangyang Wang

Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization

Qi Zhu, Carl Yang, Yidan Xu, Haonan Wang, Chao Zhang

Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence

Qi Qi, Youzhi Luo, Zhao Xu, Shuiwang Ji, Tianbao Yang