NeurIPS 2022

2,834 papers

A New Family of Generalization Bounds Using Samplewise Evaluated CMI

Fredrik Hellström, Giuseppe Durisi

Scalable design of Error-Correcting Output Codes using Discrete Optimization with Graph Coloring

Samarth Gupta, Saurabh Amin

VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training

Zhan Tong, Yibing Song, Jue Wang, Limin Wang

Hard ImageNet: Segmentations for Objects with Strong Spurious Cues

Mazda Moayeri, Sahil Singla, Soheil Feizi

Momentum Adversarial Distillation: Handling Large Distribution Shifts in Data-Free Knowledge Distillation

Kien Do, Thai Hung Le, Dung Nguyen, Dang Nguyen, HARIPRIYA HARIKUMAR

Distribution-Informed Neural Networks for Domain Adaptation Regression

Jun Wu, Jingrui He, Sheng wang, Kaiyu Guan, Elizabeth Ainsworth

LION: Latent Point Diffusion Models for 3D Shape Generation

xiaohui zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany

Nonnegative Tensor Completion via Integer Optimization

Caleb Bugg, Chen Chen, Anil Aswani

You Never Stop Dancing: Non-freezing Dance Generation via Bank-constrained Manifold Projection

Jiangxin Sun, CHUNYU WANG, Huang Hu, Hanjiang Lai, Zhi Jin

Analyzing Sharpness along GD Trajectory: Progressive Sharpening and Edge of Stability

Zixuan Wang, Zhouzi Li, Jian Li

GhostNetV2: Enhance Cheap Operation with Long-Range Attention

Yehui Tang, Kai Han, Jianyuan Guo, Chang Xu, Chao Xu

Robustness to Unbounded Smoothness of Generalized SignSGD

Michael Crawshaw, Mingrui Liu, Francesco Orabona, Wei Zhang, Zhenxun Zhuang

Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation

Josh Gardner, Zoran Popovic, Ludwig Schmidt

Joint Entropy Search for Multi-Objective Bayesian Optimization

Ben Tu, Axel Gandy, Nikolas Kantas, Behrang Shafei

A Simple Approach to Automated Spectral Clustering

Jicong Fan, Yiheng Tu, Zhao Zhang, Mingbo Zhao, Haijun Zhang

Risk-Driven Design of Perception Systems

Anthony Corso, Sydney Katz, Craig Innes, Xin Du, Subramanian Ramamoorthy

Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting

Yong Liu, Haixu Wu, Jianmin Wang, Mingsheng Long

On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach

Dennis Wei, Rahul Nair, Amit Dhurandhar, Kush R Varshney, Elizabeth Daly

Sparse Structure Search for Delta Tuning

Shengding Hu, Zhen Zhang, Ning Ding, Yadao Wang, Yasheng Wang

Theoretically Better and Numerically Faster Distributed Optimization with Smoothness-Aware Quantization Techniques

Bokun Wang, Mher Safaryan, Peter Richtarik

ZeroC: A Neuro-Symbolic Model for Zero-shot Concept Recognition and Acquisition at Inference Time

Tailin Wu, Megan Tjandrasuwita, Zhengxuan Wu, Xuelin Yang, Kevin Liu

Dataset Distillation using Neural Feature Regression

Yongchao Zhou, Ehsan Nezhadarya, Jimmy Ba

RainNet: A Large-Scale Imagery Dataset and Benchmark for Spatial Precipitation Downscaling

Xuanhong Chen, Kairui Feng, Naiyuan Liu, Bingbing Ni, Yifan Lu

Information bottleneck theory of high-dimensional regression: relevancy, efficiency and optimality

Vudtiwat Ngampruetikorn, David J Schwab

Learning single-index models with shallow neural networks

Alberto Bietti, Joan Bruna, Clayton Sanford, Min Jae Song

Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures

Shitong Luo, Yufeng Su, Xingang Peng, Sheng wang, Jian Peng

Rethinking the Reverse-engineering of Trojan Triggers

Zhenting Wang, Kai Mei, Hailun Ding, Juan Zhai, Shiqing Ma

Effective Backdoor Defense by Exploiting Sensitivity of Poisoned Samples

Weixin Chen, Baoyuan Wu, Haoqian Wang

On Margins and Generalisation for Voting Classifiers

Felix Biggs, Valentina Zantedeschi, Benjamin Guedj

Composition Theorems for Interactive Differential Privacy

Xin Lyu

Simple and Optimal Greedy Online Contention Resolution Schemes

Vasilis Livanos

Safety Guarantees for Neural Network Dynamic Systems via Stochastic Barrier Functions

Rayan Mazouz, Karan Muvvala, Akash Ratheesh Babu, Luca Laurenti, Morteza Lahijanian

On the Adversarial Robustness of Mixture of Experts

Joan Puigcerver, Rodolphe Jenatton, Carlos Riquelme, Pranjal Awasthi, Srinadh Bhojanapalli

Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs

Djordje Miladinovic, Kumar Shridhar, Kushal Jain, Max Paulus, Joachim M Buhmann

A Deep Reinforcement Learning Framework for Column Generation

Cheng Chi, Amine Aboussalah, Elias Khalil, Juyoung Wang, Zoha Sherkat-Masoumi

TVLT: Textless Vision-Language Transformer

Zineng Tang, Jaemin Cho, Yixin Nie, Mohit Bansal

Hyperparameter Sensitivity in Deep Outlier Detection: Analysis and a Scalable Hyper-Ensemble Solution

Xueying Ding, Lingxiao Zhao, Leman Akoglu

Statistical Learning and Inverse Problems: A Stochastic Gradient Approach

Yuri Fonseca, Yuri Saporito

Few-shot Learning for Feature Selection with Hilbert-Schmidt Independence Criterion

Atsutoshi Kumagai, Tomoharu Iwata, Yasutoshi Ida, Yasuhiro Fujiwara

Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts

Basil Mustafa, Carlos Riquelme, Joan Puigcerver, Rodolphe Jenatton, Neil Houlsby

Matching in Multi-arm Bandit with Collision

YiRui Zhang, Siwei Wang, Zhixuan Fang

COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamics

LIANHUI Qin, Sean Welleck, Daniel Khashabi, Yejin Choi

Data-Driven Conditional Robust Optimization

Abhilash Reddy Chenreddy, Nymisha Bandi, Erick Delage

Object Scene Representation Transformer

Mehdi S. M. Sajjadi, Daniel Duckworth, Aravindh Mahendran, Sjoerd van Steenkiste, Filip Pavetic

Is this the Right Neighborhood? Accurate and Query Efficient Model Agnostic Explanations

Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Karthikeyan Shanmugam

Lifting the Information Ratio: An Information-Theoretic Analysis of Thompson Sampling for Contextual Bandits

Gergely Neu, Iuliia Olkhovskaia, Matteo Papini, Ludovic Schwartz

Learning Distinct and Representative Modes for Image Captioning

Qi Chen, Chaorui Deng, Qi Wu

Defining and Characterizing Reward Gaming

Joar Skalse, Nikolaus Howe, Dmitrii Krasheninnikov, David Krueger

Learning Mixed Multinomial Logits with Provable Guarantees

Yiqun Hu, David Simchi-Levi, Zhenzhen Yan

Harmonizing the object recognition strategies of deep neural networks with humans

Thomas FEL, Ivan F Rodriguez Rodriguez, Drew Linsley, Thomas Serre

Public Wisdom Matters! Discourse-Aware Hyperbolic Fourier Co-Attention for Social Text Classification

Karish Grover, S M Phaneendra Angara, Md Shad Akhtar, Tanmoy Chakraborty

Learning sparse features can lead to overfitting in neural networks

Leonardo Petrini, Francesco Cagnetta, Eric Vanden-Eijnden, Matthieu Wyart

Characterizing the Ventral Visual Stream with Response-Optimized Neural Encoding Models

Meenakshi Khosla, Keith Jamison, Amy Kuceyeski, Mert Sabuncu

Deep Generalized Schrödinger Bridge

Guan-Horng Liu, Tianrong Chen, Oswin So, Evangelos Theodorou

Squeezeformer: An Efficient Transformer for Automatic Speech Recognition

Sehoon Kim, Amir Gholami, Albert Shaw, Nicholas Lee, Karttikeya Mangalam

pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning

Daoyuan Chen, Dawei Gao, Weirui Kuang, Yaliang Li, Bolin Ding

Phase Transition from Clean Training to Adversarial Training

Yue Xing, Qifan Song, Guang Cheng

Stochastic Window Transformer for Image Restoration

Jie Xiao, Xueyang Fu, Feng Wu, Zheng-Jun Zha

Augmented RBMLE-UCB Approach for Adaptive Control of Linear Quadratic Systems

Akshay Mete, Rahul Singh, P. R. Kumar

ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models

Chunyuan Li, Haotian Liu, Liunian Li, Pengchuan Zhang, Jyoti Aneja

Adversarial training for high-stakes reliability

Daniel Ziegler, Seraphina Nix, Lawrence Chan, Tim Bauman, Peter Schmidt-Nielsen

Beyond the Best: Distribution Functional Estimation in Infinite-Armed Bandits

Yifei Wang, Tavor Baharav, Yanjun Han, Jiantao Jiao, David Tse

OPEN: Orthogonal Propagation with Ego-Network Modeling

Liang Yang, Lina Kang, Qiuliang Zhang, Mengzhe Li, bingxin niu

Fast Mixing of Stochastic Gradient Descent with Normalization and Weight Decay

Zhiyuan Li, Tianhao Wang, Dingli Yu

Off-Policy Evaluation for Action-Dependent Non-stationary Environments

Yash Chandak, Shiv Shankar, Nathaniel Bastian, Bruno da Silva, Emma Brunskill

OLIVES Dataset: Ophthalmic Labels for Investigating Visual Eye Semantics

Mohit Prabhushankar, Kiran Kokilepersaud, Yash-yee Logan, Stephanie Trejo Corona, Ghassan AlRegib

Learning interacting dynamical systems with latent Gaussian process ODEs

Çağatay Yıldız, Melih Kandemir, Barbara Rakitsch

Equivariant Graph Hierarchy-Based Neural Networks

Jiaqi Han, Wenbing Huang, Tingyang Xu, Yu Rong

Learning Efficient Vision Transformers via Fine-Grained Manifold Distillation

Zhiwei Hao, Jianyuan Guo, Ding Jia, Kai Han, Yehui Tang

Learning from Few Samples: Transformation-Invariant SVMs with Composition and Locality at Multiple Scales

Tao Liu, P. R. Kumar, Ruida Zhou, Xi Liu

The Sample Complexity of One-Hidden-Layer Neural Networks

Gal Vardi, Ohad Shamir, Nati Srebro

DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detection

Lewei Yao, Jianhua Han, Youpeng Wen, Xiaodan Liang, Dan Xu

Constrained Update Projection Approach to Safe Policy Optimization

Long Yang, Jiaming Ji, Juntao Dai, Linrui Zhang, Binbin Zhou

Neural Stochastic Control

Jingdong Zhang, Qunxi Zhu, Wei LIN

“Why Not Other Classes?”: Towards Class-Contrastive Back-Propagation Explanations

Yipei Wang, Xiaoqian Wang

Are GANs overkill for NLP?

David Alvarez-Melis, Vikas Garg, Adam Kalai

MultiScan: Scalable RGBD scanning for 3D environments with articulated objects

Yongsen Mao, Yiming Zhang, Hanxiao Jiang, Angel Chang, Manolis Savva

Giga-scale Kernel Matrix-Vector Multiplication on GPU

Robert Hu, Siu Lun Chau, Dino Sejdinovic, Joan Glaunès

Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning

Dilip Arumugam, Benjamin Van Roy

SAViT: Structure-Aware Vision Transformer Pruning via Collaborative Optimization

Chuanyang Zheng, zheyang li, Kai Zhang, Zhi Yang, Wenming Tan

A Statistical Online Inference Approach in Averaged Stochastic Approximation

Chuhan Xie, Zhihua Zhang

Amortized Proximal Optimization

Juhan Bae, Paul Vicol, Jeff Z. HaoChen, Roger B Grosse

GraB: Finding Provably Better Data Permutations than Random Reshuffling

Yucheng Lu, Wentao Guo, Christopher M De Sa

Are Defenses for Graph Neural Networks Robust?

Felix Mujkanovic, Simon Geisler, Stephan Günnemann, Aleksandar Bojchevski

Time-Conditioned Dances with Simplicial Complexes: Zigzag Filtration Curve based Supra-Hodge Convolution Networks for Time-series Forecasting

Yuzhou Chen, Yulia Gel, H. Vincent Poor

Towards Disentangling Information Paths with Coded ResNeXt

Apostolos Avranas, Marios Kountouris

AutoWS-Bench-101: Benchmarking Automated Weak Supervision with 100 Labels

Nicholas Roberts, Xintong Li, Tzu-Heng Huang, Dyah Adila, Spencer Schoenberg

SoundSpaces 2.0: A Simulation Platform for Visual-Acoustic Learning

Changan Chen, Carl Schissler, Sanchit Garg, Philip Kobernik, Alexander Clegg

ShapeCrafter: A Recursive Text-Conditioned 3D Shape Generation Model

Rao Fu, Xiao Zhan, Daniel Ritchie, Srinath Sridhar, Yi-Wen Chen

Improving Generative Adversarial Networks via Adversarial Learning in Latent Space

Yang Li, Yichuan Mo, Liangliang Shi, Junchi Yan

Human-AI Shared Control via Policy Dissection

Quanyi Li, Zhenghao Peng, Haibin Wu, Lan Feng, Bolei Zhou

DTG-SSOD: Dense Teacher Guidance for Semi-Supervised Object Detection

Gang Li, Xiang Li, Yujie Wang, Wu Yichao, Ding Liang

Policy Gradient With Serial Markov Chain Reasoning

Edoardo Cetin, Oya Celiktutan

Alleviating Adversarial Attacks on Variational Autoencoders with MCMC

Anna Kuzina, Max Welling, Jakub Tomczak

VICRegL: Self-Supervised Learning of Local Visual Features

Adrien Bardes, Jean Ponce, Yann LeCun

Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs

Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann

FlowHMM: Flow-based continuous hidden Markov models

Pawel Lorek, Rafal Nowak, Tomasz Trzcinski, Maciej Zieba

Simulation-guided Beam Search for Neural Combinatorial Optimization

Jinho Choo, Yeong-Dae Kwon, Jihoon Kim, Jeongwoo Jae, André Hottung

Learning to Discover and Detect Objects

Vladimir Fomenko, Ismail Elezi, Deva Ramanan, Laura Leal-Taixé, Aljosa Osep

An efficient graph generative model for navigating ultra-large combinatorial synthesis libraries

Aryan Pedawi, Pawel Gniewek, Chaoyi Chang, Brandon Anderson, Henry van den Bedem