NeurIPS 2022

2,834 papers

On the Double Descent of Random Features Models Trained with SGD

Fanghui Liu, Johan Suykens, Volkan Cevher

PerfectDou: Dominating DouDizhu with Perfect Information Distillation

Guan Yang, Minghuan Liu, Weijun Hong, Weinan Zhang, Fei Fang

Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization

Weijia Zhang, Xuanhui Zhang, hanwen deng, Min-ling Zhang

Chartalist: Labeled Graph Datasets for UTXO and Account-based Blockchains

Kiarash Shamsi, Friedhelm Victor, Murat Kantarcioglu, Yulia Gel, Cuneyt G Akcora

Understanding Robust Learning through the Lens of Representation Similarities

Christian Cianfarani, Arjun Nitin Bhagoji, Vikash Sehwag, Ben Zhao, Heather Zheng

Fully Convolutional One-Stage 3D Object Detection on LiDAR Range Images

Zhi Tian, Xiangxiang Chu, Xiaoming Wang, Xiaolin Wei, Chunhua Shen

Recruitment Strategies That Take a Chance

Gregory Kehne, Ariel D Procaccia, Jingyan Wang

Transformer-based Working Memory for Multiagent Reinforcement Learning with Action Parsing

Yaodong Yang, Guangyong Chen, Weixun Wang, Xiaotian Hao, Jianye Hao

Improving Certified Robustness via Statistical Learning with Logical Reasoning

Zhuolin Yang, Zhikuan Zhao, Boxin Wang, Jiawei Zhang, Linyi Li

Rethinking Value Function Learning for Generalization in Reinforcement Learning

Seungyong Moon, JunYeong Lee, Hyun Oh Song

Doubly Robust Counterfactual Classification

Kwangho Kim, Edward Kennedy, Jose Zubizarreta

Cache-Augmented Inbatch Importance Resampling for Training Recommender Retriever

Jin Chen, Defu Lian, Yucheng Li, Baoyun Wang, Kai Zheng

Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients

Kyurae Kim, Jisu Oh, Jacob Gardner, Adji Bousso Dieng, Hongseok Kim

Globally Gated Deep Linear Networks

Qianyi Li, Haim Sompolinsky

Learning on the Edge: Online Learning with Stochastic Feedback Graphs

Emmanuel Esposito, Federico Fusco, Dirk van der Hoeven, Nicolò Cesa-bianchi

How to talk so AI will learn: Instructions, descriptions, and autonomy

Theodore Sumers, Robert Hawkins, Mark K Ho, Tom Griffiths, Dylan Hadfield-Menell

Bootstrapped Transformer for Offline Reinforcement Learning

Kerong Wang, Hanye Zhao, Xufang Luo, Kan Ren, Weinan Zhang

Optimal-er Auctions through Attention

Dmitry Ivanov, Iskander Safiulin, Igor Filippov, Ksenia Balabaeva

Multi-modal Grouping Network for Weakly-Supervised Audio-Visual Video Parsing

Shentong Mo, Yapeng Tian

Learning Manifold Dimensions with Conditional Variational Autoencoders

Yijia Zheng, Tong He, Yixuan Qiu, David P. Wipf, David P Wipf

Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction

Kaifeng Lyu, Zhiyuan Li, Sanjeev Arora

Towards Practical Few-shot Query Sets: Transductive Minimum Description Length Inference

Ségolène Martin, Malik Boudiaf, Emilie Chouzenoux, Jean-Christophe Pesquet, Ismail Ayed

Asymptotic Behaviors of Projected Stochastic Approximation: A Jump Diffusion Perspective

Jiadong Liang, Yuze Han, Xiang Li, Zhihua Zhang

Towards Understanding Grokking: An Effective Theory of Representation Learning

Ziming Liu, Ouail Kitouni, Niklas S Nolte, Eric Michaud, Max Tegmark

HYPRO: A Hybridly Normalized Probabilistic Model for Long-Horizon Prediction of Event Sequences

Siqiao Xue, Xiaoming Shi, James Zhang, Hongyuan Mei

Implicit Bias of Gradient Descent on Reparametrized Models: On Equivalence to Mirror Descent

Zhiyuan Li, Tianhao Wang, Jason Lee, Sanjeev Arora

Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions

Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu

On the Representation Collapse of Sparse Mixture of Experts

Zewen Chi, Li Dong, Shaohan Huang, Damai Dai, Shuming Ma

Factuality Enhanced Language Models for Open-Ended Text Generation

Nayeon Lee, Wei Ping, Peng Xu, Mostofa Patwary, Pascale N Fung

CS-Shapley: Class-wise Shapley Values for Data Valuation in Classification

Stephanie Schoch, Haifeng Xu, Yangfeng Ji

Chefs' Random Tables: Non-Trigonometric Random Features

Valerii Likhosherstov, Krzysztof M Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamas Sarlos

Regularized Gradient Descent Ascent for Two-Player Zero-Sum Markov Games

Sihan Zeng, Thinh Doan, Justin Romberg

Concrete Score Matching: Generalized Score Matching for Discrete Data

Chenlin Meng, Kristy Choi, Jiaming Song, Stefano Ermon

Graph Neural Network Bandits

Parnian Kassraie, Andreas Krause, Ilija Bogunovic

Local Latent Space Bayesian Optimization over Structured Inputs

Natalie Maus, Haydn Jones, Juston Moore, Matt J Kusner, John Bradshaw

Distributed Online Convex Optimization with Compressed Communication

Zhipeng Tu, Xi Wang, Yiguang Hong, Lei Wang, Deming Yuan

Unsupervised Reinforcement Learning with Contrastive Intrinsic Control

Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran

Enhancing Safe Exploration Using Safety State Augmentation

Aivar Sootla, Alexander Cowen-Rivers, Jun Wang, Haitham Bou Ammar

Q-ViT: Accurate and Fully Quantized Low-bit Vision Transformer

Yanjing Li, Sheng Xu, Baochang Zhang, Xianbin Cao, peng gao

PatchComplete: Learning Multi-Resolution Patch Priors for 3D Shape Completion on Unseen Categories

Yuchen Rao, Yinyu Nie, Angela Dai

Hyperbolic Feature Augmentation via Distribution Estimation and Infinite Sampling on Manifolds

Zhi Gao, Yuwei Wu, Yunde Jia, Mehrtash Harandi

Robustness Analysis of Video-Language Models Against Visual and Language Perturbations

Madeline Schiappa, Shruti Vyas, Hamid Palangi, Yogesh Rawat, Vibhav Vineet

Remember the Past: Distilling Datasets into Addressable Memories for Neural Networks

Zhiwei Deng, Olga Russakovsky

Temporal Effective Batch Normalization in Spiking Neural Networks

Chaoteng Duan, Jianhao Ding, Shiyan Chen, Zhaofei Yu, Tiejun Huang

WeightedSHAP: analyzing and improving Shapley based feature attributions

Yongchan Kwon, James Y Zou

Fairness Reprogramming

Guanhua Zhang, Yihua Zhang, Yang Zhang, Wenqi Fan, Qing Li

Blessing of Depth in Linear Regression: Deeper Models Have Flatter Landscape Around the True Solution

Jianhao Ma, Salar Fattahi

On Image Segmentation With Noisy Labels: Characterization and Volume Properties of the Optimal Solutions to Accuracy and Dice

Marcus Nordstrom, Henrik Hult, Fredrik Löfman, Jonas Söderberg

Invariance-Aware Randomized Smoothing Certificates

Jan Schuchardt, Stephan Günnemann

Visual correspondence-based explanations improve AI robustness and human-AI team accuracy

Mohammad Reza Taesiri, Giang Nguyen, Anh Nguyen

Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare

Shengpu Tang, Maggie Makar, Michael Sjoding, Finale Doshi-velez, Jenna Wiens

PALMER: Perception - Action Loop with Memory for Long-Horizon Planning

Onur Beker, Mohammad Mohammadi, Amir Zamir

On the generalization of learning algorithms that do not converge

Nisha Chandramoorthy, Andreas Loukas, Khashayar Gatmiry, Stefanie Jegelka

Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy

Jordan Awan, Jinshuo Dong

AutoMTL: A Programming Framework for Automating Efficient Multi-Task Learning

Lijun Zhang, Xiao Liu, Hui Guan

A Quantitative Geometric Approach to Neural-Network Smoothness

Zi Wang, Gautam Prakriya, Somesh Jha

Distilling Representations from GAN Generator via Squeeze and Span

Yu Yang, Xiaotian Cheng, Chang Liu, Hakan Bilen, Xiangyang Ji

Black-box coreset variational inference

Dionysis Manousakas, Hippolyt Ritter, Theofanis Karaletsos

Structuring Representations Using Group Invariants

Mehran Shakerinava, Arnab Kumar Mondal, Siamak Ravanbakhsh

Understanding Aesthetics with Language: A Photo Critique Dataset for Aesthetic Assessment

Daniel Vera Nieto, Luigi Celona, Clara Fernandez Labrador

Adv-Attribute: Inconspicuous and Transferable Adversarial Attack on Face Recognition

Shuai Jia, Bangjie Yin, Taiping Yao, Shouhong Ding, Chunhua Shen

On Learning Fairness and Accuracy on Multiple Subgroups

Changjian Shui, Gezheng Xu, Qi Chen, Jiaqi Li, Charles X. Ling

A Practical, Progressively-Expressive GNN

Lingxiao Zhao, Neil Shah, Leman Akoglu

Self-Supervised Learning via Maximum Entropy Coding

Xin Liu, Zhongdao Wang, Ya-Li Li, Shengjin Wang

Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition

Yifan Zhang, Bryan Hooi, Lanqing Hong, Jiashi Feng

Learning dynamics of deep linear networks with multiple pathways

Jianghong Shi, Eric Shea-Brown, Michael Buice

Real-Valued Backpropagation is Unsuitable for Complex-Valued Neural Networks

Zhi-Hao Tan, Yi Xie, Yuan Jiang, Zhi-Hua Zhou

Explainable Reinforcement Learning via Model Transforms

Mira Finkelstein, Nitsan levy, Lucy Liu, Yoav Kolumbus, David C. Parkes

Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective

Rongzhe Wei, Haoteng YIN, Junteng Jia, Austin R Benson, Pan Li

Sparse Hypergraph Community Detection Thresholds in Stochastic Block Model

Erchuan Zhang, David Suter, Giang Truong, Syed Zulqarnain Gilani

VoxGRAF: Fast 3D-Aware Image Synthesis with Sparse Voxel Grids

Katja Schwarz, Axel Sauer, Michael Niemeyer, Yiyi Liao, Andreas Geiger

A Unified Framework for Deep Symbolic Regression

Mikel Landajuela, Chak Shing Lee, Jiachen Yang, Ruben Glatt, Claudio P Santiago

Near-Optimal Goal-Oriented Reinforcement Learning in Non-Stationary Environments

Liyu Chen, Haipeng Luo

The trade-offs of model size in large recommendation models : 100GB to 10MB Criteo-tb DLRM model

Aditya Desai, Anshumali Shrivastava

Improving Intrinsic Exploration with Language Abstractions

Jesse Mu, Victor Zhong, Roberta Raileanu, Minqi Jiang, Noah Goodman

SPoVT: Semantic-Prototype Variational Transformer for Dense Point Cloud Semantic Completion

Sheng Yu Huang, Hao-Yu Hsu, Frank Wang

When are Local Queries Useful for Robust Learning?

Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell

Finite-Time Last-Iterate Convergence for Learning in Multi-Player Games

Yang Cai, Argyris Oikonomou, Weiqiang Zheng

Structural Analysis of Branch-and-Cut and the Learnability of Gomory Mixed Integer Cuts

Maria-Florina F Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik

Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection without Clean Datasets

Ruisi Cai, Zhenyu Zhang, Tianlong Chen, Xiaohan Chen, Zhangyang Wang

Why do We Need Large Batchsizes in Contrastive Learning? A Gradient-Bias Perspective

Changyou Chen, Jianyi Zhang, Yi Xu, Liqun Chen, Jiali Duan

Robust Neural Posterior Estimation and Statistical Model Criticism

Daniel Ward, Patrick Cannon, Mark Beaumont, Matteo Fasiolo, Sebastian Schmon

The Franz-Parisi Criterion and Computational Trade-offs in High Dimensional Statistics

Afonso S Bandeira, Ahmed El Alaoui, Samuel Hopkins, Tselil Schramm, Alexander S Wein

Relaxing Equivariance Constraints with Non-stationary Continuous Filters

Tycho van der Ouderaa, David W. Romero, Mark van der Wilk

A Boosting Approach to Reinforcement Learning

Nataly Brukhim, Elad Hazan, Karan Singh

A Simple and Optimal Policy Design for Online Learning with Safety against Heavy-tailed Risk

David Simchi-Levi, Zeyu Zheng, Feng Zhu

Bridging the Gap between Object and Image-level Representations for Open-Vocabulary Detection

Hanoona Bangalath, Muhammad Maaz, Muhammad Uzair Khattak, Salman H Khan, Fahad Shahbaz Khan

Monocular Dynamic View Synthesis: A Reality Check

Hang Gao, Ruilong Li, Shubham Tulsiani, Bryan Russell, Angjoo Kanazawa

ReCo: Retrieve and Co-segment for Zero-shot Transfer

Gyungin Shin, Weidi Xie, Samuel Albanie

Rethinking the compositionality of point clouds through regularization in the hyperbolic space

Antonio Montanaro, Diego Valsesia, Enrico Magli

Optimal Transport of Classifiers to Fairness

Maarten Buyl, Tijl De Bie

Knowledge Distillation from A Stronger Teacher

Tao Huang, Shan You, Fei Wang, Chen Qian, Chang Xu

Near-Optimal Correlation Clustering with Privacy

Vincent Cohen-Addad, Chenglin Fan, Silvio Lattanzi, Slobodan Mitrovic, Ashkan Norouzi-Fard

Distributionally Robust Optimization with Data Geometry

Jiashuo Liu, Jiayun Wu, Bo Li, Peng Cui

Random Normalization Aggregation for Adversarial Defense

Minjing Dong, Xinghao Chen, Yunhe Wang, Chang Xu

VICE: Variational Interpretable Concept Embeddings

Lukas Muttenthaler, Charles Y Zheng, Patrick McClure, Robert A Vandermeulen, Martin N Hebart

Deep Ensembles Work, But Are They Necessary?

Taiga Abe, Estefany Kelly Buchanan, Geoff Pleiss, Richard S. Zemel, John P. Cunningham

Stability and Generalization of Kernel Clustering: from Single Kernel to Multiple Kernel

Weixuan Liang, Xinwang Liu, Yong Liu, sihang zhou, Jun-Jie Huang

Optimizing Relevance Maps of Vision Transformers Improves Robustness

Hila Chefer, Idan Schwartz, Lior Wolf

The least-control principle for local learning at equilibrium

Alexander Meulemans, Nicolas Zucchet, Seijin Kobayashi, Johannes von Oswald, João Sacramento