NeurIPS 2022

2,834 papers

A Unifying Framework for Online Optimization with Long-Term Constraints

Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Giulia Romano, Nicola Gatti

DropCov: A Simple yet Effective Method for Improving Deep Architectures

Qilong Wang, Mingze Gao, Zhaolin Zhang, Jiangtao Xie, Peihua Li

Turning the Tables: Biased, Imbalanced, Dynamic Tabular Datasets for ML Evaluation

Sérgio Jesus, José Pombal, Duarte Alves, André Cruz, Pedro Saleiro

Learning Robust Rule Representations for Abstract Reasoning via Internal Inferences

Wenbo Zhang, likai tang, Site Mo, Xianggen Liu, Sen Song

Multi-Granularity Cross-modal Alignment for Generalized Medical Visual Representation Learning

Fuying Wang, Yuyin Zhou, Shujun WANG, Varut Vardhanabhuti, Lequan Yu

Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization

Benjamin Dubois-Taine, Francis R. Bach, Quentin Berthet, Adrien Taylor

Universally Expressive Communication in Multi-Agent Reinforcement Learning

Matthew Morris, Thomas D Barrett, Arnu Pretorius

Optimal Gradient Sliding and its Application to Optimal Distributed Optimization Under Similarity

Dmitry Kovalev, Aleksandr Beznosikov, Ekaterina Borodich, Alexander Gasnikov, Gesualdo Scutari

Provably sample-efficient RL with side information about latent dynamics

Yao Liu, Dipendra Misra, Miro Dudik, Robert E. Schapire

Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback

Tiancheng Jin, Tal Lancewicki, Haipeng Luo, Yishay Mansour, Aviv Rosenberg

Collaborative Decision Making Using Action Suggestions

Dylan Asmar, Mykel J Kochenderfer

Distributed Inverse Constrained Reinforcement Learning for Multi-agent Systems

Shicheng Liu, Minghui Zhu

Toward a realistic model of speech processing in the brain with self-supervised learning

Juliette MILLET, Charlotte Caucheteux, pierre orhan, Yves Boubenec, Alexandre Gramfort

MetricFormer: A Unified Perspective of Correlation Exploring in Similarity Learning

Jiexi Yan, Erkun Yang, Cheng Deng, Heng Huang

LBD: Decouple Relevance and Observation for Individual-Level Unbiased Learning to Rank

Mouxiang Chen, Chenghao Liu, Zemin Liu, Jianling Sun

FreGAN: Exploiting Frequency Components for Training GANs under Limited Data

mengping yang, Zhe Wang, Ziqiu Chi, Yanbing Zhang

MOVE: Unsupervised Movable Object Segmentation and Detection

Adam Bielski, Paolo Favaro

Neural Approximation of Graph Topological Features

Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang

Learning Concept Credible Models for Mitigating Shortcuts

Jiaxuan Wang, Sarah Jabbour, Maggie Makar, Michael Sjoding, Jenna Wiens

Point Transformer V2: Grouped Vector Attention and Partition-based Pooling

Xiaoyang Wu, Yixing Lao, Li Jiang, Xihui Liu, Hengshuang Zhao

Personalized Online Federated Learning with Multiple Kernels

Pouya M. Ghari, Yanning Shen

Mix and Reason: Reasoning over Semantic Topology with Data Mixing for Domain Generalization

Chaoqi Chen, Luyao Tang, Feng Liu, Gangming Zhao, Yue Huang

Efficient Scheduling of Data Augmentation for Deep Reinforcement Learning

Byungchan Ko, Jungseul Ok

Dense Interspecies Face Embedding

Sejong Yang, Subin Jeon, Seonghyeon Nam, Seon Joo Kim

Learning Two-Player Markov Games: Neural Function Approximation and Correlated Equilibrium

Chris Junchi Li, Dongruo Zhou, Quanquan Gu, Michael I. Jordan

Block-Recurrent Transformers

DeLesley Hutchins, Imanol Schlag, Yuhuai Wu, Ethan Dyer, Behnam Neyshabur

Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent

Yiping Lu, Jose Blanchet, Lexing Ying

Is one annotation enough? - A data-centric image classification benchmark for noisy and ambiguous label estimation

Lars Schmarje, Vasco Grossmann, Claudius Zelenka, Sabine Dippel, Rainer Kiko

Active Learning with Safety Constraints

Romain Camilleri, Andrew Wagenmaker, Jamie H Morgenstern, Lalit Jain, Kevin G. Jamieson

MorphTE: Injecting Morphology in Tensorized Embeddings

Guobing Gan, Peng Zhang, Sunzhu Li, Xiuqing Lu, Benyou Wang

Finding and Listing Front-door Adjustment Sets

Hyunchai Jeong, Jin Tian, Elias Bareinboim

Oscillatory Tracking of Continuous Attractor Neural Networks Account for Phase Precession and Procession of Hippocampal Place Cells

Tianhao Chu, Zilong Ji, Junfeng Zuo, Wenhao Zhang, Tiejun Huang

Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks

Yan Scholten, Jan Schuchardt, Simon Geisler, Aleksandar Bojchevski, Stephan Günnemann

Exponential Separations in Symmetric Neural Networks

Aaron Zweig, Joan Bruna

New Definitions and Evaluations for Saliency Methods: Staying Intrinsic, Complete and Sound

Arushi Gupta, Nikunj Saunshi, Dingli Yu, Kaifeng Lyu, Sanjeev Arora

A Unified Convergence Theorem for Stochastic Optimization Methods

Xiao Li, Andre Milzarek

Robust Feature-Level Adversaries are Interpretability Tools

Stephen Casper, Max Nadeau, Dylan Hadfield-Menell, Gabriel Kreiman

Optimistic Tree Searches for Combinatorial Black-Box Optimization

Cedric Malherbe, Antoine Grosnit, Rasul Tutunov, Haitham Bou Ammar, Jun Wang

Single-pass Streaming Lower Bounds for Multi-armed Bandits Exploration with Instance-sensitive Sample Complexity

Sepehr Assadi, Chen Wang

Rank Diminishing in Deep Neural Networks

Ruili Feng, Kecheng Zheng, Yukun Huang, Deli Zhao, Michael I. Jordan

The Power and Limitation of Pretraining-Finetuning for Linear Regression under Covariate Shift

Jingfeng Wu, Difan Zou, Vladimir braverman, Quanquan Gu, Sham Kakade

Approximate Value Equivalence

Christopher Grimm, Andre Barreto, Satinder P. Singh

Hyperbolic Embedding Inference for Structured Multi-Label Prediction

Bo Xiong, Michael Cochez, Mojtaba Nayyeri, Steffen Staab

Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search

YAO SHU, Zhongxiang Dai, Zhaoxuan Wu, Bryan Kian Hsiang Low

Efficient and Effective Optimal Transport-Based Biclustering

Chakib Fettal, lazhar labiod, Mohamed NADIF

VRL3: A Data-Driven Framework for Visual Deep Reinforcement Learning

Che Wang, Xufang Luo, Keith Ross, Dongsheng Li

On the Discrimination Risk of Mean Aggregation Feature Imputation in Graphs

Arjun Subramonian, Kai-Wei Chang, Yizhou Sun

Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone

Zi-Yi Dou, Aishwarya Kamath, Zhe Gan, Pengchuan Zhang, Jianfeng Wang

Towards Better Evaluation for Dynamic Link Prediction

Farimah Poursafaei, Shenyang Huang, Kellin Pelrine, Reihaneh Rabbany

Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models

Yang Shu, ZHANGJIE CAO, Ziyang Zhang, Jianmin Wang, Mingsheng Long

VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts

Hangbo Bao, Wenhui Wang, Li Dong, Qiang Liu, Owais Khan Mohammed

PROSPECT: Labeled Tandem Mass Spectrometry Dataset for Machine Learning in Proteomics

Omar Shouman, Wassim Gabriel, Victor-George Giurcoiu, Vitor Sternlicht, Mathias Wilhelm

Grounding Aleatoric Uncertainty for Unsupervised Environment Design

Minqi Jiang, Michael Dennis, Jack Parker-Holder, Andrei Lupu, Heinrich Küttler

AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection

Marius Dragoi, Elena Burceanu, Emanuela Haller, Andrei Manolache, Florin Brad

A Neural Pre-Conditioning Active Learning Algorithm to Reduce Label Complexity

Seo Taek Kong, Soomin Jeon, Dongbin Na, Jaewon Lee, Hong-Seok Lee

Optimal Weak to Strong Learning

Kasper Green Larsen, Martin Ritzert

In What Ways Are Deep Neural Networks Invariant and How Should We Measure This?

Henry Kvinge, Tegan Emerson, Grayson Jorgenson, Scott Vasquez, Tim Doster

Global Convergence of Direct Policy Search for State-Feedback H_∞ Robust Control: A Revisit of Nonsmooth Synthesis with Goldstein Subdifferential

Xingang Guo, Bin Hu

ConfounderGAN: Protecting Image Data Privacy with Causal Confounder

Qi Tian, Kun Kuang, Kelu Jiang, Furui Liu, Zhihua Wang

Generating multivariate time series with COmmon Source CoordInated GAN (COSCI-GAN)

Ali Seyfi, Jean-Francois Rajotte, Raymond Ng

Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm

Aidan Good, Jiaqi Lin, Xin Yu, Hannah Sieg, Mikey Fergurson

Pushing the limits of fairness impossibility: Who's the fairest of them all?

Brian Hsu, Rahul Mazumder, Preetam Nandy, Kinjal Basu

Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning

Zaiyu Huang, Hanhui Li, Zhenyu Xie, Michael Kampffmeyer, qingling Cai

Multi-Objective Deep Learning with Adaptive Reference Vectors

Weiyu Chen, James T. Kwok

Benefits of Additive Noise in Composing Classes with Bounded Capacity

Alireza Fathollah Pour, Hassan Ashtiani

Object Representations as Fixed Points: Training Iterative Refinement Algorithms with Implicit Differentiation

Michael Chang, Tom Griffiths, Sergey Levine

Robust φ-Divergence MDPs

Chin Pang Ho, Marek Petrik, Wolfram Wiesemann

On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit Bias

Itay Safran, Gal Vardi, Jason Lee

D^2NeRF: Self-Supervised Decoupling of Dynamic and Static Objects from a Monocular Video

Tianhao Wu, Fangcheng Zhong, Andrea Tagliasacchi, Forrester Cole, Cengiz Oztireli

Efficient Risk-Averse Reinforcement Learning

Ido Greenberg, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor

KSD Aggregated Goodness-of-fit Test

Antonin Schrab, Benjamin Guedj, Arthur Gretton

Two-layer neural network on infinite dimensional data: global optimization guarantee in the mean-field regime

Naoki Nishikawa, Taiji Suzuki, Atsushi Nitanda, Denny Wu

OpenOOD: Benchmarking Generalized Out-of-Distribution Detection

Jingkang Yang, Pengyun Wang, Dejian Zou, Zitang Zhou, Kunyuan Ding

Transferring Fairness under Distribution Shifts via Fair Consistency Regularization

Bang An, Zora Che, Mucong Ding, Furong Huang

Improved Fine-Tuning by Better Leveraging Pre-Training Data

Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li

Synergy-of-Experts: Collaborate to Improve Adversarial Robustness

Sen Cui, Jingfeng ZHANG, Jian Liang, Bo Han, Masashi Sugiyama

A Multi-Task Benchmark for Korean Legal Language Understanding and Judgement Prediction

Wonseok Hwang, Dongjun Lee, Kyoungyeon Cho, Hanuhl Lee, Minjoon Seo

Weak-shot Semantic Segmentation via Dual Similarity Transfer

Junjie Chen, Li Niu, Siyuan Zhou, Jianlou Si, Chen Qian

Differentially Private Online-to-batch for Smooth Losses

Qinzi Zhang, Hoang Tran, Ashok Cutkosky

Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization

Wei Jiang, Gang Li, Yibo Wang, Lijun Zhang, Tianbao Yang

Average Sensitivity of Euclidean k-Clustering

Yuichi Yoshida, Shinji Ito

Estimation of Entropy in Constant Space with Improved Sample Complexity

Maryam Aliakbarpour, Andrew McGregor, Jelani Nelson, Erik Waingarten

Uncovering the Structural Fairness in Graph Contrastive Learning

Ruijia Wang, Xiao Wang, Chuan Shi, Le Song

Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions

Omri Ben-Eliezer, Dan Mikulincer, Ilias Zadik

Rethinking Individual Global Max in Cooperative Multi-Agent Reinforcement Learning

Yitian Hong, Yaochu Jin, Yang Tang

Debiased Self-Training for Semi-Supervised Learning

Baixu Chen, Junguang Jiang, Ximei Wang, Pengfei Wan, Jianmin Wang

On Robust Multiclass Learnability

Jingyuan Xu, Weiwei Liu

Let Images Give You More: Point Cloud Cross-Modal Training for Shape Analysis

Xu Yan, Heshen Zhan, Chaoda Zheng, Jiantao Gao, Ruimao Zhang

On Efficient Online Imitation Learning via Classification

Yichen Li, Chicheng Zhang

Model-based Lifelong Reinforcement Learning with Bayesian Exploration

Haotian Fu, Shangqun Yu, Michael L. Littman, George Konidaris

Autoformalization with Large Language Models

Yuhuai Wu, Albert Qiaochu Jiang, Wenda Li, Markus Rabe, Charles Staats

ZSON: Zero-Shot Object-Goal Navigation using Multimodal Goal Embeddings

Arjun Majumdar, Gunjan Aggarwal, Bhavika Devnani, Judy Hoffman, Dhruv Batra

TA-GATES: An Encoding Scheme for Neural Network Architectures

Xuefei Ning, Zixuan Zhou, Junbo Zhao, Tianchen Zhao, Yiping Deng

Efficient coding, channel capacity, and the emergence of retinal mosaics

Na Young Jun, Greg Field, John C. Pearson

Deep Combinatorial Aggregation

Yuesong Shen, Daniel Cremers

First is Better Than Last for Language Data Influence

Chih-Kuan Yeh, Ankur Taly, Mukund Sundararajan, Frederick Liu, Pradeep K Ravikumar

Maximum Likelihood Training of Implicit Nonlinear Diffusion Model

Dongjun Kim, Byeonghu Na, Se Jung Kwon, Dongsoo Lee, Wanmo Kang

Provably expressive temporal graph networks

Amauri Souza, Diego Mesquita, Samuel Kaski, Vikas Garg

Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks

Blake Bordelon, Cengiz Pehlevan

Compositional generalization through abstract representations in human and artificial neural networks

Takuya Ito, Tim Klinger, Doug Schultz, John Murray, Michael Cole