NeurIPS 2022

2,834 papers

EHRSQL: A Practical Text-to-SQL Benchmark for Electronic Health Records

Gyubok Lee, Hyeonji Hwang, Seongsu Bae, Yeonsu Kwon, Woncheol Shin

VeriDark: A Large-Scale Benchmark for Authorship Verification on the Dark Web

Andrei Manolache, Florin Brad, Antonio Barbalau, Radu Tudor Ionescu, Marius Popescu

K-LITE: Learning Transferable Visual Models with External Knowledge

Sheng Shen, Chunyuan Li, Xiaowei Hu, Yujia Xie, Jianwei Yang

Watermarking for Out-of-distribution Detection

qizhou wang, Feng Liu, Yonggang Zhang, Jing Zhang, Chen Gong

A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs

Fabian Falck, Christopher K. I. Williams, Dominic Danks, George Deligiannidis, Christopher Yau

Weakly Supervised Representation Learning with Sparse Perturbations

Kartik Ahuja, Jason S Hartford, Yoshua Bengio

Efficient Meta Reinforcement Learning for Preference-based Fast Adaptation

Zhizhou Ren, Anji Liu, Yitao Liang, Jian Peng, Jianzhu Ma

TPU-KNN: K Nearest Neighbor Search at Peak FLOP/s

Felix Chern, Blake Hechtman, Andy Davis, Ruiqi Guo, David Majnemer

STaR: Bootstrapping Reasoning With Reasoning

Eric Zelikman, Yuhuai Wu, Jesse Mu, Noah Goodman

LasUIE: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language Model

Hao Fei, Shengqiong Wu, Jingye Li, Bobo Li, Fei Li

Stability Analysis and Generalization Bounds of Adversarial Training

Jiancong Xiao, Yanbo Fan, Ruoyu Sun, Jue Wang, Zhi-Quan Luo

SoftPatch: Unsupervised Anomaly Detection with Noisy Data

Xi Jiang, Jianlin Liu, Jinbao Wang, Qiang Nie, Kai WU

NUWA-Infinity: Autoregressive over Autoregressive Generation for Infinite Visual Synthesis

Jian Liang, Chenfei Wu, Xiaowei Hu, Zhe Gan, Jianfeng Wang

Off-Team Learning

Brandon Cui, Hengyuan Hu, Andrei Lupu, Samuel Sokota, Jakob Foerster

PKD: General Distillation Framework for Object Detectors via Pearson Correlation Coefficient

Weihan Cao, Yifan Zhang, Jianfei Gao, Anda Cheng, Ke Cheng

Private and Communication-Efficient Algorithms for Entropy Estimation

Gecia Bravo-Hermsdorff, Róbert Busa-Fekete, Mohammad Ghavamzadeh, Andres Munoz Medina, Umar Syed

Bi-directional Weakly Supervised Knowledge Distillation for Whole Slide Image Classification

Linhao Qu, xiaoyuan luo, Manning Wang, Zhijian Song

Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model

Gen Li, Yuejie Chi, Yuting Wei, Yuxin Chen

Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions

Nikolaos Karalias, Joshua W. Robinson, Andreas Loukas, Stefanie Jegelka

Logical Credal Networks

Radu Marinescu, Haifeng Qian, Alexander G. Gray, Debarun Bhattacharjya, Francisco Barahona

Retrieval-Augmented Diffusion Models

Andreas Blattmann, Robin Rombach, Kaan Oktay, Jonas Müller, Bjorn Ommer

LASSIE: Learning Articulated Shapes from Sparse Image Ensemble via 3D Part Discovery

Chun-Han Yao, Wei-Chih Hung, Yuanzhen Li, Michael Rubinstein, Ming-Hsuan Yang

Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity

Abhishek Gupta, Aldo Pacchiano, Yuexiang Zhai, Sham Kakade, Sergey Levine

PointTAD: Multi-Label Temporal Action Detection with Learnable Query Points

Jing Tan, Xiaotong Zhao, Xintian Shi, Bin Kang, Limin Wang

Unsupervised Object Representation Learning using Translation and Rotation Group Equivariant VAE

Alireza Nasiri, Tristan Bepler

Drawing out of Distribution with Neuro-Symbolic Generative Models

Yichao Liang, Josh Tenenbaum, Tuan Anh Le, Siddharth N

Inductive Logical Query Answering in Knowledge Graphs

Michael Galkin, Zhaocheng Zhu, Hongyu Ren, Jian Tang

NeuForm: Adaptive Overfitting for Neural Shape Editing

Connor Lin, Niloy Mitra, Gordon Wetzstein, Leonidas Guibas, Paul Guerrero

Order-Invariant Cardinality Estimators Are Differentially Private

Charlie Dickens, Justin Thaler, Daniel Ting

DreamShard: Generalizable Embedding Table Placement for Recommender Systems

Daochen Zha, Louis Feng, Qiaoyu Tan, Zirui Liu, Kwei-Herng Lai

Variance Reduced ProxSkip: Algorithm, Theory and Application to Federated Learning

Grigory Malinovsky, Kai Yi, Peter Richtarik

Rethinking Variational Inference for Probabilistic Programs with Stochastic Support

Tim Reichelt, Luke Ong, Thomas Rainforth

Structure-Preserving 3D Garment Modeling with Neural Sewing Machines

Xipeng Chen, Guangrun Wang, Dizhong Zhu, Xiaodan Liang, Philip Torr

Scalable and Efficient Non-adaptive Deterministic Group Testing

Dariusz Kowalski, Dominik Pajak

Learning to Share in Networked Multi-Agent Reinforcement Learning

Yuxuan Yi, Ge Li, Yaowei Wang, Zongqing Lu

Deliberated Domain Bridging for Domain Adaptive Semantic Segmentation

Lin Chen, Zhixiang Wei, Xin Jin, Huaian Chen, Miao Zheng

Improving GANs with A Dynamic Discriminator

Ceyuan Yang, Yujun Shen, Yinghao Xu, Deli Zhao, Bo Dai

Decentralized, Communication- and Coordination-free Learning in Structured Matching Markets

Chinmay Maheshwari, Shankar Sastry, Eric Mazumdar

Periodic Graph Transformers for Crystal Material Property Prediction

Keqiang Yan, Yi Liu, Yuchao Lin, Shuiwang Ji

GriddlyJS: A Web IDE for Reinforcement Learning

Christopher Bamford, Minqi Jiang, Mikayel Samvelyan, Tim Rocktäschel

Beyond spectral gap: the role of the topology in decentralized learning

Thijs Vogels, Hadrien Hendrikx, Martin Jaggi

Independence Testing for Bounded Degree Bayesian Networks

Arnab Bhattacharyya, Clément L Canonne, Qiping Yang

Network change point localisation under local differential privacy

Mengchu Li, Tom Berrett, Yi Yu

Near-Optimal Multi-Agent Learning for Safe Coverage Control

Manish Prajapat, Matteo Turchetta, Melanie Zeilinger, Andreas Krause

Sequence-to-Set Generative Models

Longtao Tang, Ying Zhou, Yu Yang

Keypoint-Guided Optimal Transport with Applications in Heterogeneous Domain Adaptation

Xiang Gu, Yucheng Yang, Wei Zeng, Jian Sun, Zongben Xu

HUMANISE: Language-conditioned Human Motion Generation in 3D Scenes

Zan Wang, Yixin Chen, Tengyu Liu, Yixin Zhu, Wei Liang

Retaining Knowledge for Learning with Dynamic Definition

Zichang Liu, Benjamin Coleman, Tianyi Zhang, Anshumali Shrivastava

Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks

Sizhe Chen, Zhehao Huang, Qinghua Tao, Yingwen Wu, Cihang Xie

Less-forgetting Multi-lingual Fine-tuning

Yuren Mao, Yaobo Liang, Nan Duan, Haobo Wang, Kai Wang

Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms

Xutong Liu, Jinhang Zuo, Siwei Wang, Carlee Joe-Wong, John C.S. Lui

Don't Pour Cereal into Coffee: Differentiable Temporal Logic for Temporal Action Segmentation

Ziwei Xu, Yogesh Rawat, Yongkang Wong, Mohan S Kankanhalli, Mubarak Shah

Semi-Discrete Normalizing Flows through Differentiable Tessellation

Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel

On Gap-dependent Bounds for Offline Reinforcement Learning

Xinqi Wang, Qiwen Cui, Simon S Du

Learning Modular Simulations for Homogeneous Systems

Jayesh Gupta, Sai Vemprala, Ashish Kapoor

Injecting Domain Knowledge from Empirical Interatomic Potentials to Neural Networks for Predicting Material Properties

Zeren Shui, Daniel Karls, Mingjian Wen, ilia Nikiforov, Ellad Tadmor

Hardness in Markov Decision Processes: Theory and Practice

Michelangelo Conserva, Paulo Rauber

Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data

Allen Nie, Yannis Flet-Berliac, Deon Jordan, William Steenbergen, Emma Brunskill

Compressible-composable NeRF via Rank-residual Decomposition

Jiaxiang Tang, Xiaokang Chen, Jingbo Wang, Gang Zeng

You Only Live Once: Single-Life Reinforcement Learning

Annie Chen, Archit Sharma, Sergey Levine, Chelsea Finn

A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal

Yaqian Zhang, Bernhard Pfahringer, Eibe Frank, Albert Bifet, Nick Jin Sean Lim

VaiPhy: a Variational Inference Based Algorithm for Phylogeny

Hazal Koptagel, Oskar Kviman, Harald Melin, Negar Safinianaini, Jens Lagergren

Saliency-Aware Neural Architecture Search

Ramtin Hosseini, Pengtao Xie

CoupAlign: Coupling Word-Pixel with Sentence-Mask Alignments for Referring Image Segmentation

Zicheng Zhang, Yi Zhu, Jianzhuang Liu, Xiaodan Liang, Wei Ke

Diffusion Models as Plug-and-Play Priors

Alexandros Graikos, Nikolay Malkin, Nebojsa Jojic, Dimitris Samaras

Provable Defense against Backdoor Policies in Reinforcement Learning

Shubham Bharti, Xuezhou Zhang, Adish Singla, Xiaojin Zhu

The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization

Dmitry Kovalev, Alexander Gasnikov

Private Set Generation with Discriminative Information

Dingfan Chen, Raouf Kerkouche, Mario Fritz

Bridging the Gap Between Vision Transformers and Convolutional Neural Networks on Small Datasets

Zhiying Lu, Hongtao Xie, Chuanbin Liu, Yongdong Zhang

FP8 Quantization: The Power of the Exponent

Andrey Kuzmin, Mart van Baalen, Yuwei Ren, Markus Nagel, Jorn Peters

Learning the Structure of Large Networked Systems Obeying Conservation Laws

Anirudh Rayas, Rajasekhar Anguluri, Gautam Dasarathy

NeurOLight: A Physics-Agnostic Neural Operator Enabling Parametric Photonic Device Simulation

Jiaqi Gu, Zhengqi Gao, Chenghao Feng, Hanqing Zhu, Ray Chen

Using Mixup as a Regularizer Can Surprisingly Improve Accuracy & Out-of-Distribution Robustness

Francesco Pinto, Harry Yang, Ser Nam Lim, Philip Torr, Puneet Dokania

Orthogonal Transformer: An Efficient Vision Transformer Backbone with Token Orthogonalization

Huaibo Huang, Xiaoqiang Zhou, Ran He

Pure Transformers are Powerful Graph Learners

Jinwoo Kim, Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee

Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials

Eshaan Nichani, Yu Bai, Jason Lee

Online Bipartite Matching with Advice: Tight Robustness-Consistency Tradeoffs for the Two-Stage Model

Billy Jin, Will Ma

Fast Vision Transformers with HiLo Attention

Zizheng Pan, Jianfei Cai, Bohan Zhuang

Rare Gems: Finding Lottery Tickets at Initialization

Kartik Sreenivasan, Jy-yong Sohn, Liu Yang, Matthew Grinde, Alliot Nagle

ALIFE: Adaptive Logit Regularizer and Feature Replay for Incremental Semantic Segmentation

Youngmin Oh, Donghyeon Baek, Bumsub Ham

Recipe for a General, Powerful, Scalable Graph Transformer

Ladislav Rampášek, Michael Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf

An Embarrassingly Simple Approach to Semi-Supervised Few-Shot Learning

Xiu-Shen Wei, H.-Y. Xu, Faen Zhang, Yuxin Peng, Wei Zhou

Multi-dataset Training of Transformers for Robust Action Recognition

Junwei Liang, Enwei Zhang, Jun Zhang, Chunhua Shen

Reinforcement Learning in a Birth and Death Process: Breaking the Dependence on the State Space

Jonatha Anselmi, Bruno Gaujal, Louis-Sébastien Rebuffi

projUNN: efficient method for training deep networks with unitary matrices

Bobak Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd

Variational inference via Wasserstein gradient flows

Marc Lambert, Sinho Chewi, Francis R. Bach, Silvère Bonnabel, Philippe Rigollet

In the Eye of the Beholder: Robust Prediction with Causal User Modeling

Amir Feder, Guy Horowitz, Yoav Wald, Roi Reichart, Nir Rosenfeld

Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing

Nataniel Ruiz, Sarah Bargal, Cihang Xie, Kate Saenko, Stan Sclaroff

P2P: Tuning Pre-trained Image Models for Point Cloud Analysis with Point-to-Pixel Prompting

Ziyi Wang, Xumin Yu, Yongming Rao, Jie Zhou, Jiwen Lu

Unsupervised Domain Adaptation for Semantic Segmentation using Depth Distribution

Quanliang Wu, Huajun Liu

Are all Frames Equal? Active Sparse Labeling for Video Action Detection

Aayush Rana, Yogesh Rawat

SelecMix: Debiased Learning by Contradicting-pair Sampling

Inwoo Hwang, Sangjun Lee, Yunhyeok Kwak, Seong Joon Oh, Damien Teney

Knowledge-Aware Bayesian Deep Topic Model

Dongsheng Wang, Yi.shi Xu, Miaoge Li, Zhibin Duan, Chaojie Wang

Perturbation Learning Based Anomaly Detection

Jinyu Cai, Jicong Fan

BiT: Robustly Binarized Multi-distilled Transformer

Zechun Liu, Barlas Oguz, Aasish Pappu, Lin Xiao, Scott Yih

SemMAE: Semantic-Guided Masking for Learning Masked Autoencoders

Gang Li, Heliang Zheng, Daqing Liu, Chaoyue Wang, Bing Su

Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models

Manli Shu, Weili Nie, De-An Huang, Zhiding Yu, Tom Goldstein

On the Theoretical Properties of Noise Correlation in Stochastic Optimization

Aurelien Lucchi, Frank Proske, Antonio Orvieto, Francis R. Bach, Hans Kersting

Approximate Secular Equations for the Cubic Regularization Subproblem

Yihang Gao, Man-Chung Yue, Michael Ng

Error Analysis of Tensor-Train Cross Approximation

Zhen Qin, Alexander Lidiak, Zhexuan Gong, Gongguo Tang, Michael B Wakin