NeurIPS 2022

2,834 papers

Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods

Randall Balestriero, Yann LeCun

Toward Understanding Privileged Features Distillation in Learning-to-Rank

Shuo Yang, Sujay Sanghavi, Holakou Rahmanian, Jan Bakus, Vishwanathan S. V. N.

CoPur: Certifiably Robust Collaborative Inference via Feature Purification

Jing Liu, Chulin Xie, Sanmi Koyejo, Bo Li

SMPL: Simulated Industrial Manufacturing and Process Control Learning Environments

Mohan Zhang, Xiaozhou Wang, Benjamin Decardi-Nelson, Bo Song, An Zhang

The Gyro-Structure of Some Matrix Manifolds

Xuan Son Nguyen

DARE: Disentanglement-Augmented Rationale Extraction

Linan Yue, Qi Liu, Yichao Du, Yanqing An, Li Wang

Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent

Soon Hoe Lim, Yijun Wan, Umut Simsekli

TREC: Transient Redundancy Elimination-based Convolution

Jiawei Guan, Feng Zhang, Jiesong Liu, Hsin-Hsuan Sung, Ruofan Wu

Elucidating the Design Space of Diffusion-Based Generative Models

Tero Karras, Miika Aittala, Timo Aila, Samuli Laine

WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language Models

Yonatan Bitton, Nitzan Bitton Guetta, Ron Yosef, Yuval Elovici, Mohit Bansal

Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning

Wenhao Ding, Haohong Lin, Bo Li, Ding Zhao

On the Effectiveness of Fine-tuning Versus Meta-reinforcement Learning

Mandi Zhao, Pieter Abbeel, Stephen James

Can Adversarial Training Be Manipulated By Non-Robust Features?

Lue Tao, Lei Feng, Hongxin Wei, Jinfeng Yi, Sheng-jun Huang

Temporally Disentangled Representation Learning

Weiran Yao, Guangyi Chen, Kun Zhang

Distilled Gradient Aggregation: Purify Features for Input Attribution in the Deep Neural Network

Giyoung Jeon, Haedong Jeong, Jaesik Choi

ST-Adapter: Parameter-Efficient Image-to-Video Transfer Learning

Junting Pan, Ziyi Lin, Xiatian Zhu, Jing Shao, hongsheng Li

Few-Shot Non-Parametric Learning with Deep Latent Variable Model

Zhiying Jiang, Yiqin Dai, Ji Xin, Ming Li, Jimmy Lin

Neural Abstractions

Alessandro Abate, Alec Edwards, Mirco Giacobbe

Wukong: A 100 Million Large-scale Chinese Cross-modal Pre-training Benchmark

Jiaxi Gu, Xiaojun Meng, Guansong Lu, Lu Hou, Niu Minzhe

Automatic differentiation of nonsmooth iterative algorithms

Jérôme Bolte, Edouard Pauwels, Samuel Vaiter

SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collections

Mark Boss, Andreas Engelhardt, Abhishek Kar, Yuanzhen Li, Deqing Sun

Coresets for Wasserstein Distributionally Robust Optimization Problems

Ruomin Huang, Jiawei Huang, Wenjie Liu, Hu Ding

IMED-RL: Regret optimal learning of ergodic Markov decision processes

Fabien Pesquerel, Odalric-ambrym Maillard

The Policy-gradient Placement and Generative Routing Neural Networks for Chip Design

Ruoyu Cheng, Xianglong Lyu, Yang Li, Junjie Ye, Jianye Hao

HyperTree Proof Search for Neural Theorem Proving

Guillaume Lample, Timothee Lacroix, Marie-Anne Lachaux, Aurelien Rodriguez, Amaury Hayat

Proximal Learning With Opponent-Learning Awareness

Stephen Zhao, Chris Lu, Roger B Grosse, Jakob Foerster

Rotation-Equivariant Conditional Spherical Neural Fields for Learning a Natural Illumination Prior

James Gardner, Bernhard Egger, William Smith

UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes

Alexander Kolesnikov, André Susano Pinto, Lucas Beyer, Xiaohua Zhai, Jeremiah Harmsen

Learn what matters: cross-domain imitation learning with task-relevant embeddings

Tim Franzmeyer, Philip Torr, João F. Henriques

DiSC: Differential Spectral Clustering of Features

Ram Dyuthi Sristi, Gal Mishne, Ariel Jaffe

Learning Physical Dynamics with Subequivariant Graph Neural Networks

Jiaqi Han, Wenbing Huang, Hengbo Ma, Jiachen Li, Josh Tenenbaum

Learning Expressive Meta-Representations with Mixture of Expert Neural Processes

Qi Wang, Herke van Hoof

On the Tradeoff Between Robustness and Fairness

Xinsong Ma, Zekai Wang, Weiwei Liu

On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models

Kamil Deja, Anna Kuzina, Tomasz Trzcinski, Jakub Tomczak

A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks

Mingrui Liu, Zhenxun Zhuang, Yunwen Lei, Chunyang Liao

Generalized Delayed Feedback Model with Post-Click Information in Recommender Systems

Jiaqi Yang, De-Chuan Zhan

Multilingual Abusive Comment Detection at Scale for Indic Languages

Vikram Gupta, Sumegh Roychowdhury, Mithun Das, Somnath Banerjee, Punyajoy Saha

Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization

Tianyi Lin, Zeyu Zheng, Michael I. Jordan

Chromatic Correlation Clustering, Revisited

Qing Xiu, Kai Han, Jing Tang, Shuang Cui, He Huang

On the Generalization Power of the Overfitted Three-Layer Neural Tangent Kernel Model

Peizhong Ju, Xiaojun Lin, Ness Shroff

Efficient Submodular Optimization under Noise: Local Search is Robust

Lingxiao Huang, Yuyi Wang, Chunxue Yang, Huanjian Zhou

PeRFception: Perception using Radiance Fields

Yoonwoo Jeong, Seungjoo Shin, Junha Lee, Chris Choy, Anima Anandkumar

Deep Hierarchical Planning from Pixels

Danijar Hafner, Kuang-Huei Lee, Ian Fischer, Pieter Abbeel

A Mixture Of Surprises for Unsupervised Reinforcement Learning

Andrew Zhao, Matthieu Lin, Yangguang Li, Yong-jin Liu, Gao Huang

Diversified Recommendations for Agents with Adaptive Preferences

William Brown, Arpit Agarwal

TTOpt: A Maximum Volume Quantized Tensor Train-based Optimization and its Application to Reinforcement Learning

Konstantin Sozykin, Andrei Chertkov, Roman Schutski, Anh-Huy Phan, Ivan Oseledets

Benchmarking and Analyzing 3D Human Pose and Shape Estimation Beyond Algorithms

Hui En Pang, Zhongang Cai, Lei Yang, Tianwei Zhang, Ziwei Liu

Empirical Phase Diagram for Three-layer Neural Networks with Infinite Width

Hanxu Zhou, Zhou Qixuan, Zhenyuan Jin, Tao Luo, Yaoyu Zhang

Semi-supervised Semantic Segmentation with Prototype-based Consistency Regularization

Haiming Xu, Lingqiao Liu, Qiuchen Bian, Zhen Yang

Evaluation beyond Task Performance: Analyzing Concepts in AlphaZero in Hex

Charles Lovering, Jessica Forde, George Konidaris, Ellie Pavlick, Michael L. Littman

Open High-Resolution Satellite Imagery: The WorldStrat Dataset – With Application to Super-Resolution

Julien Cornebise, Ivan Oršolić, Freddie Kalaitzis

Infinite-Fidelity Coregionalization for Physical Simulation

Shibo Li, Zheng Wang, Robert Kirby, Shandian Zhe

Efficient Training of Low-Curvature Neural Networks

Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju, Francois Fleuret

Distinguishing Learning Rules with Brain Machine Interfaces

Jacob Portes, Christian Schmid, James M Murray

A contrastive rule for meta-learning

Nicolas Zucchet, Simon Schug, Johannes von Oswald, Dominic Zhao, João Sacramento

Online Agnostic Multiclass Boosting

Vinod Raman, Ambuj Tewari

CLEAR: Generative Counterfactual Explanations on Graphs

Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li

Multi-view Subspace Clustering on Topological Manifold

Shudong Huang, Hongjie Wu, Yazhou Ren, Ivor W. Tsang, Zenglin Xu

Toward Efficient Robust Training against Union of ℓ_p Threat Models

Gaurang Sriramanan, Maharshi Gor, Soheil Feizi

Distributionally Adaptive Meta Reinforcement Learning

Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal

Rapidly Mixing Multiple-try Metropolis Algorithms for Model Selection Problems

Hyunwoong Chang, Changwoo Lee, Zhao Tang Luo, Huiyan Sang, Quan Zhou

Gradient Estimation with Discrete Stein Operators

Jiaxin Shi, Yuhao Zhou, Jessica Hwang, Michalis K. Titsias, Lester W. Mackey

Linear tree shap

peng yu, Albert Bifet, Jesse Read, Chao Xu

Branch & Learn for Recursively and Iteratively Solvable Problems in Predict+Optimize

Xinyi Hu, Jasper Lee, Jimmy Lee, Allen Z. Zhong

BigBio: A Framework for Data-Centric Biomedical Natural Language Processing

Jason Fries, Leon Weber, Natasha Seelam, Gabriel Altay, Debajyoti Datta

When are Offline Two-Player Zero-Sum Markov Games Solvable?

Qiwen Cui, Simon S Du

A Closer Look at Prototype Classifier for Few-shot Image Classification

Mingcheng Hou, Issei Sato

Fast Algorithms for Packing Proportional Fairness and its Dual

Francisco Criado, David Martínez-Rubio, Sebastian Pokutta

Deep Model Reassembly

Xingyi Yang, Daquan Zhou, Songhua Liu, Jingwen Ye, Xinchao Wang

Online PAC-Bayes Learning

Maxime Haddouche, Benjamin Guedj

Fast Bayesian Estimation of Point Process Intensity as Function of Covariates

Hideaki Kim, Taichi Asami, Hiroyuki Toda

Semi-supervised Vision Transformers at Scale

Zhaowei Cai, Avinash Ravichandran, Paolo Favaro, Manchen Wang, Davide Modolo

Improving Diffusion Models for Inverse Problems using Manifold Constraints

Hyungjin Chung, Byeongsu Sim, Dohoon Ryu, Jong Chul Ye

SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles

Chejian Xu, Wenhao Ding, Weijie Lyu, ZUXIN LIU, Shuai Wang

Non-Linear Coordination Graphs

Yipeng Kang, Tonghan Wang, Qianlan Yang, Xiaoran Wu, Chongjie Zhang

Optimal Efficiency-Envy Trade-Off via Optimal Transport

Steven Yin, Christian Kroer

Improved Utility Analysis of Private CountSketch

Rasmus Pagh, Mikkel Thorup

Perfect Sampling from Pairwise Comparisons

Dimitris Fotakis, Alkis Kalavasis, Christos Tzamos

A Neural Corpus Indexer for Document Retrieval

Yujing Wang, Yingyan Hou, Haonan Wang, Ziming Miao, Shibin Wu

Brain Network Transformer

Xuan Kan, Wei Dai, Hejie Cui, Zilong Zhang, Ying Guo

NSNet: A General Neural Probabilistic Framework for Satisfiability Problems

Zhaoyu Li, Xujie Si

Ziyi Chen, Shaocong Ma, Yi Zhou

Confident Approximate Policy Iteration for Efficient Local Planning in q^π-realizable MDPs

Gellert Weisz, András György, Tadashi Kozuno, Csaba Szepesvári

DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems

Ruizhong Qiu, Zhiqing Sun, Yiming Yang

Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification

Dandan Guo, Zhuo Li, meixi zheng, He Zhao, Mingyuan Zhou

Learning Recourse on Instance Environment to Enhance Prediction Accuracy

Lokesh N, Guntakanti Sai Koushik, Abir De, Sunita Sarawagi

Neural Payoff Machines: Predicting Fair and Stable Payoff Allocations Among Team Members

Daphne Cornelisse, Thomas Rood, Yoram Bachrach, Mateusz Malinowski, Tal Kachman

Cross Aggregation Transformer for Image Restoration

Zheng Chen, Yulun Zhang, Jinjin Gu, yongbing zhang, Linghe Kong

Decentralized Training of Foundation Models in Heterogeneous Environments

Binhang Yuan, Yongjun He, Jared Davis, Tianyi Zhang, Tri Dao

Conservative Dual Policy Optimization for Efficient Model-Based Reinforcement Learning

Shenao Zhang

Deep Attentive Belief Propagation: Integrating Reasoning and Learning for Solving Constraint Optimization Problems

Yanchen Deng, Shufeng Kong, Caihua Liu, Bo An

SketchBoost: Fast Gradient Boosted Decision Tree for Multioutput Problems

Leonid Iosipoi, Anton Vakhrushev

Benchopt: Reproducible, efficient and collaborative optimization benchmarks

Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier

Earthformer: Exploring Space-Time Transformers for Earth System Forecasting

Zhihan Gao, Xingjian SHI, Hao Wang, Yi Zhu, Yuyang (Bernie) Wang

Semantic Exploration from Language Abstractions and Pretrained Representations

Allison Tam, Neil Rabinowitz, Andrew Lampinen, Nicholas A. Roy, Stephanie Chan

Online Deep Equilibrium Learning for Regularization by Denoising

Jiaming Liu, Xiaojian Xu, Weijie Gan, shirin shoushtari, Ulugbek Kamilov

High-dimensional limit theorems for SGD: Effective dynamics and critical scaling

Gerard Ben Arous, Reza Gheissari, Aukosh Jagannath

Disentangling the Predictive Variance of Deep Ensembles through the Neural Tangent Kernel

Seijin Kobayashi, Pau Vilimelis Aceituno, Johannes von Oswald

A Damped Newton Method Achieves Global $\mathcal O \left(\frac{1}{k^2}\right)$ and Local Quadratic Convergence Rate

Slavomír Hanzely, Dmitry Kamzolov, Dmitry Pasechnyuk, Alexander Gasnikov, Peter Richtarik

HUMUS-Net: Hybrid Unrolled Multi-scale Network Architecture for Accelerated MRI Reconstruction

Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi