NeurIPS 2022

2,834 papers

Learning with little mixing

Ingvar Ziemann, Stephen Tu

Generative Status Estimation and Information Decoupling for Image Rain Removal

Di Lin, Xin Wang, Jia Shen, Renjie Zhang, Ruonan Liu

UnfoldML: Cost-Aware and Uncertainty-Based Dynamic 2D Prediction for Multi-Stage Classification

Yanbo Xu, Alind Khare, Glenn Matlin, Monish Ramadoss, Rishikesan Kamaleswaran

Constrained GPI for Zero-Shot Transfer in Reinforcement Learning

Jaekyeom Kim, Seohong Park, Gunhee Kim

A Unified Model for Multi-class Anomaly Detection

Zhiyuan You, Lei Cui, Yujun Shen, Kai Yang, Xin Lu

Precise Learning Curves and Higher-Order Scalings for Dot-product Kernel Regression

Lechao Xiao, Hong Hu, Theodor Misiakiewicz, Yue Lu, Jeffrey Pennington

Self-Supervised Learning Through Efference Copies

Franz Scherr, Qinghai Guo, Timoleon Moraitis

On the detrimental effect of invariances in the likelihood for variational inference

Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang (Bernie) Wang, Jan Gasthaus

Delving into Sequential Patches for Deepfake Detection

Jiazhi Guan, Hang Zhou, Zhibin Hong, Errui Ding, Jingdong Wang

Association Graph Learning for Multi-Task Classification with Category Shifts

Jiayi Shen, Zehao Xiao, Xiantong Zhen, Cees Snoek, Marcel Worring

Challenging Common Assumptions in Convex Reinforcement Learning

Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli

Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning

Elias Frantar, Dan Alistarh

Rethinking Image Restoration for Object Detection

Shangquan Sun, Wenqi Ren, Tao Wang, Xiaochun Cao

Divert More Attention to Vision-Language Tracking

Mingzhe Guo, Zhipeng Zhang, Heng Fan, Liping Jing

Optimal Rates for Regularized Conditional Mean Embedding Learning

Zhu Li, Dimitri Meunier, Mattes Mollenhauer, Arthur Gretton

On the Generalizability and Predictability of Recommender Systems

Duncan McElfresh, Sujay Khandagale, Jonathan Valverde, John Dickerson, Colin White

Polynomial Neural Fields for Subband Decomposition and Manipulation

Guandao Yang, Sagie Benaim, Varun Jampani, Kyle Genova, Jonathan Barron

Asynchronous Actor-Critic for Multi-Agent Reinforcement Learning

Yuchen Xiao, Weihao Tan, Christopher Amato

Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power

Binghui Li, Jikai Jin, Han Zhong, John Hopcroft, Liwei Wang

Energy-Based Contrastive Learning of Visual Representations

Beomsu Kim, Jong Chul Ye

Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure

Paul Novello, Thomas FEL, David Vigouroux

Diffusion-LM Improves Controllable Text Generation

Xiang Li, John Thickstun, Ishaan Gulrajani, Percy Liang, Tatsunori B Hashimoto

Redundancy-Free Message Passing for Graph Neural Networks

Rongqin Chen, Shenghui Zhang, Leong Hou U, Ye Li

Your Transformer May Not be as Powerful as You Expect

Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-yan Liu, Liwei Wang

SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression

Zhize Li, Haoyu Zhao, Boyue Li, Yuejie Chi

Resource-Adaptive Federated Learning with All-In-One Neural Composition

Yiqun Mei, Pengfei Guo, Mo Zhou, Vishal Patel

Global Normalization for Streaming Speech Recognition in a Modular Framework

Ehsan Variani, Ke Wu, Michael D Riley, David Rybach, Matt Shannon

NeMF: Neural Motion Fields for Kinematic Animation

Chengan He, Jun Saito, James Zachary, Holly Rushmeier, Yi Zhou

Robust Streaming PCA

Daniel Bienstock, Minchan Jeong, Apurv Shukla, Se-Young Yun

HSurf-Net: Normal Estimation for 3D Point Clouds by Learning Hyper Surfaces

Qing Li, Yu-Shen Liu, Jin-San Cheng, Cheng Wang, Yi Fang

Focal Modulation Networks

Jianwei Yang, Chunyuan Li, Xiyang Dai, Jianfeng Gao

Spartan: Differentiable Sparsity via Regularized Transportation

Kai Sheng Tai, Taipeng Tian, Ser Nam Lim

Generalization Analysis on Learning with a Concurrent Verifier

Masaaki Nishino, Kengo Nakamura, Norihito Yasuda

A General Framework for Auditing Differentially Private Machine Learning

Fred Lu, Joseph Munoz, Maya Fuchs, Tyler LeBlond, Elliott Zaresky-Williams

Equivariant Networks for Crystal Structures

Oumar Kaba, Siamak Ravanbakhsh

On the Convergence Theory for Hessian-Free Bilevel Algorithms

Daouda Sow, Kaiyi Ji, Yingbin Liang

Matrix Multiplicative Weights Updates in Quantum Zero-Sum Games: Conservation Laws & Recurrence

Rahul Jain, Georgios Piliouras, Ryann Sim

VectorAdam for Rotation Equivariant Geometry Optimization

Selena Zihan Ling, Nicholas Sharp, Alec Jacobson

Sample-Efficient Learning of Correlated Equilibria in Extensive-Form Games

Ziang Song, Song Mei, Yu Bai

A Policy-Guided Imitation Approach for Offline Reinforcement Learning

Haoran Xu, Li Jiang, Li Jianxiong, Xianyuan Zhan

Oracle-Efficient Online Learning for Smoothed Adversaries

Nika Haghtalab, Yanjun Han, Abhishek Shetty, Kunhe Yang

On Enforcing Better Conditioned Meta-Learning for Rapid Few-Shot Adaptation

Markus Hiller, Mehrtash Harandi, Tom Drummond

CARLANE: A Lane Detection Benchmark for Unsupervised Domain Adaptation from Simulation to multiple Real-World Domains

Bonifaz Stuhr, Johann Haselberger, Julian Gebele

Self-supervised surround-view depth estimation with volumetric feature fusion

Jung-Hee Kim, Junhwa Hur, Tien Phuoc Nguyen, Seong-Gyun Jeong

Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces

Vladimir Kostic, Pietro Novelli, Andreas Maurer, Carlo Ciliberto, Lorenzo Rosasco

Uncalibrated Models Can Improve Human-AI Collaboration

Kailas Vodrahalli, Tobias Gerstenberg, James Y Zou

Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency

Xiang Zhang, Ziyuan Zhao, Theodoros Tsiligkaridis, Marinka Zitnik

Quasi-Newton Methods for Saddle Point Problems

Chengchang Liu, Luo Luo

Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world

Eugene Vinitsky, Nathan Lichtlé, Xiaomeng Yang, Brandon Amos, Jakob Foerster

USB: A Unified Semi-supervised Learning Benchmark for Classification

Yidong Wang, Hao Chen, Yue Fan, Wang SUN, Ran Tao

Flare7K: A Phenomenological Nighttime Flare Removal Dataset

Yuekun Dai, Chongyi Li, Shangchen Zhou, Ruicheng Feng, Chen Change Loy

Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions

Haanvid Lee, Jongmin Lee, Yunseon Choi, Wonseok Jeon, Byung-Jun Lee

Graph Convolution Network based Recommender Systems: Learning Guarantee and Item Mixture Powered Strategy

Leyan Deng, Defu Lian, Chenwang Wu, Enhong Chen

Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning

Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex M Lamb, Kenji Kawaguchi

Thompson Sampling Efficiently Learns to Control Diffusion Processes

Mohamad Kazem Shirani Faradonbeh, Mohamad Sadegh Shirani Faradonbeh, Mohsen Bayati

Structural Knowledge Distillation for Object Detection

Philip de Rijk, Lukas Schneider, Marius Cordts, Dariu Gavrila

Solving Quantitative Reasoning Problems with Language Models

Aitor Lewkowycz, Anders Andreassen, David Dohan, Ethan Dyer, Henryk Michalewski

Asymmetric Temperature Scaling Makes Larger Networks Teach Well Again

Xin-Chun Li, Wen-shu Fan, Shaoming Song, Yinchuan Li, bingshuai Li

K-Radar: 4D Radar Object Detection for Autonomous Driving in Various Weather Conditions

Dong-Hee Paek, SEUNG-HYUN KONG, Kevin Tirta Wijaya

Theseus: A Library for Differentiable Nonlinear Optimization

Luis Pineda, Taosha Fan, Maurizio Monge, Shobha Venkataraman, Paloma Sodhi

Privacy of Noisy Stochastic Gradient Descent: More Iterations without More Privacy Loss

Jason Altschuler, Kunal Talwar

"Lossless" Compression of Deep Neural Networks: A High-dimensional Neural Tangent Kernel Approach

lingyu gu, Yongqi Du, yuan zhang, Di Xie, Shiliang Pu

A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases

James Harrison, Luke Metz, Jascha Sohl-dickstein

SCAMPS: Synthetics for Camera Measurement of Physiological Signals

Daniel McDuff, Miah Wander, Xin Liu, Brian Hill, Javier Hernandez

Communicating Natural Programs to Humans and Machines

Sam Acquaviva, Yewen Pu, Marta Kryven, Theodoros Sechopoulos, Catherine Wong

Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning

Veit David Wild, Robert Hu, Dino Sejdinovic

Dynamic Fair Division with Partial Information

Gerdus Benade, Daniel Halpern, Alexandros Psomas

Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems

Abishek Thangamuthu, Gunjan Kumar, Suresh Bishnoi, Ravinder Bhattoo, N M Anoop Krishnan

Causal Identification under Markov equivalence: Calculus, Algorithm, and Completeness

Amin Jaber, Adele Ribeiro, Jiji Zhang, Elias Bareinboim

Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization?

Rishi Bommasani, Kathleen A. Creel, Ananya Kumar, Dan Jurafsky, Percy Liang

Reinforcement Learning with Non-Exponential Discounting

Matthias Schultheis, Constantin A Rothkopf, Heinz Koeppl

Frank-Wolfe-based Algorithms for Approximating Tyler's M-estimator

Lior Danon, Dan Garber

Cryptographic Hardness of Learning Halfspaces with Massart Noise

Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi, Lisheng Ren

EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations

Min Zhao, Fan Bao, Chongxuan Li, Jun Zhu

Stimulative Training of Residual Networks: A Social Psychology Perspective of Loafing

Peng Ye, Shengji Tang, Baopu Li, Tao Chen, Wanli Ouyang

Rethinking Generalization in Few-Shot Classification

Markus Hiller, Rongkai Ma, Mehrtash Harandi, Tom Drummond

CalFAT: Calibrated Federated Adversarial Training with Label Skewness

Chen Chen, Yuchen Liu, Xingjun Ma, Lingjuan Lyu

Unsupervised Point Cloud Completion and Segmentation by Generative Adversarial Autoencoding Network

Changfeng Ma, Yang Yang, Jie Guo, Fei Pan, Chongjun Wang

Learning Predictions for Algorithms with Predictions

Misha Khodak, Maria-Florina F Balcan, Ameet Talwalkar, Sergei Vassilvitskii

Better SGD using Second-order Momentum

Hoang Tran, Ashok Cutkosky

Sound and Complete Verification of Polynomial Networks

Elias Abad Rocamora, Mehmet Fatih Sahin, Fanghui Liu, Grigorios Chrysos, Volkan Cevher

CroCo: Self-Supervised Pre-training for 3D Vision Tasks by Cross-View Completion

Philippe Weinzaepfel, Vincent Leroy, Thomas Lucas, Romain BRÉGIER, Yohann Cabon

Pseudo-Riemannian Graph Convolutional Networks

Bo Xiong, Shichao Zhu, Nico Potyka, Shirui Pan, Chuan Zhou

DGD^2: A Linearly Convergent Distributed Algorithm For High-dimensional Statistical Recovery

Marie Maros, Gesualdo Scutari

Dynamic pricing and assortment under a contextual MNL demand

Noemie Perivier, Vineet Goyal

Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis

Shayegan Omidshafiei, Andrei Kapishnikov, Yannick Assogba, Lucas Dixon, Been Kim

Is Sortition Both Representative and Fair?

Soroush Ebadian, Gregory Kehne, Evi Micha, Ariel D Procaccia, Nisarg Shah

Sublinear Algorithms for Hierarchical Clustering

Arpit Agarwal, Sanjeev Khanna, Huan Li, Prathamesh Patil

Geo-Neus: Geometry-Consistent Neural Implicit Surfaces Learning for Multi-view Reconstruction

Qiancheng Fu, Qingshan Xu, Yew Soon Ong, Wenbing Tao

Consistent Interpolating Ensembles via the Manifold-Hilbert Kernel

Yutong Wang, Clay Scott

Generalised Mutual Information for Discriminative Clustering

Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Warith HARCHAOUI, Mickaël Leclercq

C-Mixup: Improving Generalization in Regression

Huaxiu Yao, Yiping Wang, Linjun Zhang, James Y Zou, Chelsea Finn

EgoTaskQA: Understanding Human Tasks in Egocentric Videos

Baoxiong Jia, Ting Lei, Song-chun Zhu, Siyuan Huang

Improving Task-Specific Generalization in Few-Shot Learning via Adaptive Vicinal Risk Minimization

Long-Kai Huang, Ying Wei

Private Multiparty Perception for Navigation

Hui Lu, Mia Chiquier, Carl Vondrick

Robust Semi-Supervised Learning when Not All Classes have Labels

Lan-Zhe Guo, Yi-Ge Zhang, Zhi-Fan Wu, Jie-Jing Shao, Yu-feng Li

Uncoupled Learning Dynamics with $O(\log T)$ Swap Regret in Multiplayer Games

Ioannis Anagnostides, Gabriele Farina, Christian Kroer, Chung-Wei Lee, Haipeng Luo

An Information-Theoretic Framework for Deep Learning

Hong Jun Jeon, Benjamin Van Roy

Contrastive Neural Ratio Estimation

Benjamin K Miller, Christoph Weniger, Patrick Forré

S3GC: Scalable Self-Supervised Graph Clustering

Fnu Devvrit, Aditya Sinha, Prateek Jain, Inderjit S Dhillon, Inderjit S. Dhillon