NeurIPS 2022

2,834 papers

ComMU: Dataset for Combinatorial Music Generation

Hyun Lee, Taehyun Kim, Hyolim Kang, Minjoo Ki, Hyeonchan Hwang

OTKGE: Multi-modal Knowledge Graph Embeddings via Optimal Transport

Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao

Near-Optimal No-Regret Learning Dynamics for General Convex Games

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

Robust Models are less Over-Confident

Julia Grabinski, Paul Gavrikov, Janis Keuper, Margret Keuper

Structural Kernel Search via Bayesian Optimization and Symbolical Optimal Transport

Matthias Bitzer, Mona Meister, Christoph Zimmer

Unsupervised Skill Discovery via Recurrent Skill Training

Zheyuan Jiang, Jingyue Gao, Jianyu Chen

Enabling Detailed Action Recognition Evaluation Through Video Dataset Augmentation

Jihoon Chung, Yu Wu, Olga Russakovsky

Geoclidean: Few-Shot Generalization in Euclidean Geometry

Joy Hsu, Jiajun Wu, Noah Goodman

Neural Transmitted Radiance Fields

Chengxuan Zhu, Renjie Wan, Boxin Shi

Cost-efficient Gaussian tensor network embeddings for tensor-structured inputs

Linjian Ma, Edgar Solomonik

You Can’t Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments

Keiran Paster, Sheila McIlraith, Jimmy Ba

Beyond L1: Faster and Better Sparse Models with skglm

Quentin Bertrand, Quentin Klopfenstein, Pierre-Antoine Bannier, Gauthier Gidel, Mathurin Massias

DASCO: Dual-Generator Adversarial Support Constrained Offline Reinforcement Learning

Quan Vuong, Aviral Kumar, Sergey Levine, Yevgen Chebotar

Graph Few-shot Learning with Task-specific Structures

Song Wang, Chen Chen, Jundong Li

Recommender Forest for Efficient Retrieval

Chao Feng, Wuchao Li, Defu Lian, Zheng Liu, Enhong Chen

Fair and Optimal Decision Trees: A Dynamic Programming Approach

Jacobus van der Linden, Mathijs de Weerdt, Emir Demirović

Breaking Bad: A Dataset for Geometric Fracture and Reassembly

Silvia Sellán, Yun-Chun Chen, Ziyi Wu, Animesh Garg, Alec Jacobson

Exploring evolution-aware & -free protein language models as protein function predictors

Mingyang Hu, Fajie Yuan, Kevin Yang, Fusong Ju, Jin Su

Explicable Policy Search

Ze Gong, Yu ("Tony") Zhang

SIXO: Smoothing Inference with Twisted Objectives

Dieterich Lawson, Allan Raventós, Andrew Warrington, Scott Linderman

FedSR: A Simple and Effective Domain Generalization Method for Federated Learning

A. Tuan Nguyen, Philip Torr, Ser Nam Lim

A Spectral Approach to Item Response Theory

Duc Nguyen, Anderson Ye Zhang

Capturing Graphs with Hypo-Elliptic Diffusions

Csaba Toth, Darrick Lee, Celia Hacker, Harald Oberhauser

JAHS-Bench-201: A Foundation For Research On Joint Architecture And Hyperparameter Search

Archit Bansal, Danny Stoll, Maciej Janowski, Arber Zela, Frank Hutter

Learning Latent Seasonal-Trend Representations for Time Series Forecasting

Zhiyuan Wang, Xovee Xu, Weifeng Zhang, Goce Trajcevski, Ting Zhong

Explicit Tradeoffs between Adversarial and Natural Distributional Robustness

Mazda Moayeri, Kiarash Banihashem, Soheil Feizi

Beyond Adult and COMPAS: Fair Multi-Class Prediction via Information Projection

Wael Alghamdi, Hsiang Hsu, Haewon Jeong, Hao Wang, Peter Michalak

A Transformer-Based Object Detector with Coarse-Fine Crossing Representations

Zhishan Li, Ying Nie, Kai Han, Jianyuan Guo, Lei Xie

Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning

Jiachen T. Wang, Saeed Mahloujifar, Shouda Wang, Ruoxi Jia, Prateek Mittal

Towards Improving Calibration in Object Detection Under Domain Shift

Muhammad Akhtar Munir, Muhammad Haris Khan, M. Sarfraz, Mohsen Ali

Error Correction Code Transformer

Yoni Choukroun, Lior Wolf

Universality of Group Convolutional Neural Networks Based on Ridgelet Analysis on Groups

Sho Sonoda, Isao Ishikawa, Masahiro Ikeda

Asymptotically Unbiased Instance-wise Regularized Partial AUC Optimization: Theory and Algorithm

HuiYang Shao, Qianqian Xu, Zhiyong Yang, Shilong Bao, Qingming Huang

Text-Adaptive Multiple Visual Prototype Matching for Video-Text Retrieval

Chengzhi Lin, Ancong Wu, Junwei Liang, Jun Zhang, Wenhang Ge

Learning-Augmented Algorithms for Online Linear and Semidefinite Programming

Elena Grigorescu, Young-San Lin, Sandeep Silwal, Maoyuan Song, Samson Zhou

MEMO: Test Time Robustness via Adaptation and Augmentation

Marvin Zhang, Sergey Levine, Chelsea Finn

Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules

Kazuki Irie, Francesco Faccio, Jürgen Schmidhuber

ASPiRe: Adaptive Skill Priors for Reinforcement Learning

Mengda Xu, Manuela M. Veloso, Shuran Song

Re-Analyze Gauss: Bounds for Private Matrix Approximation via Dyson Brownian Motion

Oren Mangoubi, Nisheeth Vishnoi

ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation

Yufei Xu, Jing Zhang, Qiming ZHANG, Dacheng Tao

Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks

Yunwen Lei, Rong Jin, Yiming Ying

Exploring Length Generalization in Large Language Models

Cem Anil, Yuhuai Wu, Anders Andreassen, Aitor Lewkowycz, Vedant Misra

Sparse2Dense: Learning to Densify 3D Features for 3D Object Detection

Tianyu Wang, Xiaowei Hu, Zhengzhe LIU, Chi-Wing Fu

On Feature Learning in the Presence of Spurious Correlations

Pavel Izmailov, Polina Kirichenko, Nate Gruver, Andrew G Wilson

MetaMask: Revisiting Dimensional Confounder for Self-Supervised Learning

Jiangmeng Li, Wenwen Qiang, Yanan Zhang, Wenyi Mo, Changwen Zheng

Graph Reordering for Cache-Efficient Near Neighbor Search

Benjamin Coleman, Santiago Segarra, Alexander J Smola, Anshumali Shrivastava

Finite-Time Regret of Thompson Sampling Algorithms for Exponential Family Multi-Armed Bandits

Tianyuan Jin, Pan Xu, Xiaokui Xiao, Anima Anandkumar

Preservation of the Global Knowledge by Not-True Distillation in Federated Learning

Gihun Lee, Minchan Jeong, Yongjin Shin, Sangmin Bae, Se-Young Yun

Multi-agent Performative Prediction with Greedy Deployment and Consensus Seeking Agents

Qiang Li, Chung-Yiu Yau, Hoi-To Wai

Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks

Hongjoon Ahn, Yongyi Yang, Quan Gan, Taesup Moon, David P. Wipf

Active Learning for Multiple Target Models

Ying-Peng Tang, Sheng-jun Huang

Communication Efficient Federated Learning for Generalized Linear Bandits

Chuanhao Li, Hongning Wang

Self-Explaining Deviations for Coordination

Hengyuan Hu, Samuel Sokota, David Wu, Anton Bakhtin, Andrei Lupu

Enhanced Latent Space Blind Model for Real Image Denoising via Alternative Optimization

Chao Ren, Yizhong Pan, Jie Huang

Operator Splitting Value Iteration

Amin Rakhsha, Andrew Wang, Mohammad Ghavamzadeh, Amir-massoud Farahmand

DABS 2.0: Improved Datasets and Algorithms for Universal Self-Supervision

Alex Tamkin, Gaurab Banerjee, Mohamed Owda, Vincent Liu, Shashank Rammoorthy

Exposing and Exploiting Fine-Grained Block Structures for Fast and Accurate Sparse Training

Peng Jiang, Lihan Hu, Shihui Song

Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients

Hualin Zhang, Huan Xiong, Bin Gu

Weakly supervised causal representation learning

Johann Brehmer, Pim de Haan, Phillip Lippe, Taco S Cohen

Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy

Zhiqi Bu, Jialin Mao, Shiyun Xu

Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization

Hui Yuan, Chengzhuo Ni, Huazheng Wang, Xuezhou Zhang, Le Cong

Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models

Kushal Tirumala, Aram Markosyan, Luke Zettlemoyer, Armen Aghajanyan

Marksman Backdoor: Backdoor Attacks with Arbitrary Target Class

Khoa D Doan, Yingjie Lao, Ping Li

Robustness Disparities in Face Detection

Samuel Dooley, George Z Wei, Tom Goldstein, John Dickerson

Learning on Arbitrary Graph Topologies via Predictive Coding

Tommaso Salvatori, Luca Pinchetti, Beren Millidge, Yuhang Song, Tianyi Bao

Double Check Your State Before Trusting It: Confidence-Aware Bidirectional Offline Model-Based Imagination

Jiafei Lyu, Xiu Li, Zongqing Lu

Sequencer: Deep LSTM for Image Classification

Yuki Tatsunami, Masato Taki

What is a Good Metric to Study Generalization of Minimax Learners?

Asuman Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang

Fine-tuning language models to find agreement among humans with diverse preferences

Michiel Bakker, Martin Chadwick, Hannah Sheahan, Michael Tessler, Lucy Campbell-Gillingham

Thinned random measures for sparse graphs with overlapping communities

Federica Zoe Ricci, Michele Guindani, Erik B. Sudderth

Weakly-Supervised Multi-Granularity Map Learning for Vision-and-Language Navigation

Peihao Chen, Dongyu Ji, Kunyang Lin, Runhao Zeng, Thomas Li

Model Zoos: A Dataset of Diverse Populations of Neural Network Models

Konstantin Schürholt, Diyar Taskiran, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth

Decentralized Local Stochastic Extra-Gradient for Variational Inequalities

Aleksandr Beznosikov, Pavel Dvurechenskii, Anastasiia Koloskova, Valentin Samokhin, Sebastian U Stich

On the Convergence of Stochastic Multi-Objective Gradient Manipulation and Beyond

Shiji Zhou, Wenpeng Zhang, Jiyan Jiang, Wenliang Zhong, Jinjie GU

Towards Effective Multi-Modal Interchanges in Zero-Resource Sounding Object Localization

Yang Zhao, Chen Zhang, Haifeng Huang, Haoyuan Li, Zhou Zhao

Neural Conservation Laws: A Divergence-Free Perspective

Jack Richter-Powell, Yaron Lipman, Ricky T. Q. Chen

Model Preserving Compression for Neural Networks

Jerry Chee, Megan Flynn (née Renz), Anil Damle, Christopher M De Sa

A new dataset for multilingual keyphrase generation

Frédéric Piedboeuf, Philippe Langlais

Long-Form Video-Language Pre-Training with Multimodal Temporal Contrastive Learning

Yuchong Sun, Hongwei Xue, Ruihua Song, Bei Liu, Huan Yang

Intermediate Prototype Mining Transformer for Few-Shot Semantic Segmentation

YUANWEI LIU, Nian Liu, Xiwen Yao, Junwei Han

Pruning Neural Networks via Coresets and Convex Geometry: Towards No Assumptions

Murad Tukan, Loay Mualem, Alaa Maalouf

Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network?

Yibo Yang, Shixiang Chen, Xiangtai Li, Liang Xie, Zhouchen Lin

Deep Equilibrium Approaches to Diffusion Models

Ashwini Pokle, Zhengyang Geng, J. Zico Kolter

Cluster Randomized Designs for One-Sided Bipartite Experiments

Jennifer Brennan, Vahab Mirrokni, Jean Pouget-Abadie

Pruning’s Effect on Generalization Through the Lens of Training and Regularization

Tian Jin, Michael Carbin, Dan Roy, Jonathan Frankle, Gintare Karolina Dziugaite

High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation

Jimmy Ba, Murat A Erdogdu, Taiji Suzuki, Zhichao Wang, Denny Wu

PAC Prediction Sets for Meta-Learning

Sangdon Park, Edgar Dobriban, Insup Lee, Osbert Bastani

The Query Complexity of Cake Cutting

Simina Branzei, Noam Nisan

Learning to Mitigate AI Collusion on Economic Platforms

Gianluca Brero, Eric Mibuari, Nicolas Lepore, David C. Parkes

The Effects of Regularization and Data Augmentation are Class Dependent

Randall Balestriero, Léon Bottou, Yann LeCun

Rethinking Resolution in the Context of Efficient Video Recognition

Chuofan Ma, Qiushan Guo, Yi Jiang, Ping Luo, Zehuan Yuan

Detecting Abrupt Changes in Sequential Pairwise Comparison Data

Wanshan Li, Alessandro Rinaldo, Daren Wang

Unsupervised Learning of Shape Programs with Repeatable Implicit Parts

Boyang Deng, Sumith Kulal, Zhengyang Dong, Congyue Deng, Yonglong Tian

Vision Transformers provably learn spatial structure

Samy Jelassi, Michael Sander, Yuanzhi Li

Self-Supervised Pretraining for Large-Scale Point Clouds

Zaiwei Zhang, Min Bai, Erran Li Li

FLAIR: Federated Learning Annotated Image Repository

Congzheng Song, Filip Granqvist, Kunal Talwar

Toward Equation of Motion for Deep Neural Networks: Continuous-time Gradient Descent and Discretization Error Analysis

Taiki Miyagawa

Deep Surrogate Assisted Generation of Environments

Varun Bhatt, Bryon Tjanaka, Matthew Fontaine, Stefanos Nikolaidis

Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imaging

Yuanhao Cai, Jing Lin, Haoqian Wang, Xin Yuan, Henghui Ding

Stability and Generalization for Markov Chain Stochastic Gradient Methods

Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou