NeurIPS 2022

2,834 papers

Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification

Ihsan Ullah, Dustin Carrión-Ojeda, Sergio Escalera, Isabelle Guyon, Mike Huisman

XTC: Extreme Compression for Pre-trained Transformers Made Simple and Efficient

Xiaoxia Wu, Zhewei Yao, Minjia Zhang, Conglong Li, Yuxiong He

Self-explaining deep models with logic rule reasoning

Seungeon Lee, Xiting Wang, Sungwon Han, Xiaoyuan Yi, Xing Xie

Online Reinforcement Learning for Mixed Policy Scopes

Junzhe Zhang, Elias Bareinboim

A Universal Error Measure for Input Predictions Applied to Online Graph Problems

Giulia Bernardini, Alexander Lindermayr, Alberto Marchetti-Spaccamela, Nicole Megow, Leen Stougie

Learning Neural Acoustic Fields

Andrew Luo, Yilun Du, Michael Tarr, Josh Tenenbaum, Antonio Torralba

Quantum Speedups of Optimizing Approximately Convex Functions with Applications to Logarithmic Regret Stochastic Convex Bandits

Tongyang Li, Ruizhe Zhang

Bellman Residual Orthogonalization for Offline Reinforcement Learning

Andrea Zanette, Martin J. Wainwright, Martin J Wainwright

Integral Probability Metrics PAC-Bayes Bounds

Ron Amit, Baruch Epstein, Shay Moran, Ron Meir

Near-Optimal Sample Complexity Bounds for Constrained MDPs

Sharan Vaswani, Lin Yang, Csaba Szepesvári

Debiased Machine Learning without Sample-Splitting for Stable Estimators

Qizhao Chen, Vasilis Syrgkanis, Morgane Austern

Learning to Break the Loop: Analyzing and Mitigating Repetitions for Neural Text Generation

Jin Xu, Xiaojiang Liu, Jianhao Yan, Deng Cai, Huayang Li

(De-)Randomized Smoothing for Decision Stump Ensembles

Miklós Horváth, Mark Müller, Marc Fischer, Martin Vechev

On A Mallows-type Model For (Ranked) Choices

Yifan Feng, Yuxuan Tang

MBW: Multi-view Bootstrapping in the Wild

Mosam Dabhi, Chaoyang Wang, Tim Clifford, László Jeni, Ian Fasel

Combining Explicit and Implicit Regularization for Efficient Learning in Deep Networks

Dan Zhao

Will Bilevel Optimizers Benefit from Loops

Kaiyi Ji, Mingrui Liu, Yingbin Liang, Lei Ying

Combinatorial Bandits with Linear Constraints: Beyond Knapsacks and Fairness

QINGSONG LIU, Weihang Xu, Siwei Wang, Zhixuan Fang

Functional Indirection Neural Estimator for Better Out-of-distribution Generalization

Kha Pham, Thai Hung Le, Man Ngo, Truyen Tran

Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum

Nian Liu, Xiao Wang, Deyu Bo, Chuan Shi, Jian Pei

DivBO: Diversity-aware CASH for Ensemble Learning

Yu Shen, Yupeng Lu, Yang Li, Yaofeng Tu, Wentao Zhang

Tree Mover's Distance: Bridging Graph Metrics and Stability of Graph Neural Networks

Ching-Yao Chuang, Stefanie Jegelka

Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity

Mucong Ding, Tahseen Rabbani, Bang An, Evan Wang, Furong Huang

Perceptual Attacks of No-Reference Image Quality Models with Human-in-the-Loop

Weixia Zhang, Dingquan Li, Xiongkuo Min, Guangtao Zhai, Guodong Guo

TransTab: Learning Transferable Tabular Transformers Across Tables

Zifeng Wang, Jimeng Sun

Sample Complexity of Learning Heuristic Functions for Greedy-Best-First and A* Search

Shinsaku Sakaue, Taihei Oki

Approximation with CNNs in Sobolev Space: with Applications to Classification

Guohao Shen, Yuling Jiao, Yuanyuan Lin, Jian Huang

Understanding Programmatic Weak Supervision via Source-aware Influence Function

Jieyu Zhang, Haonan Wang, Cheng-Yu Hsieh, Alexander J Ratner

S4ND: Modeling Images and Videos as Multidimensional Signals with State Spaces

Eric Nguyen, Karan Goel, Albert Gu, Gordon Downs, Preey Shah

What I Cannot Predict, I Do Not Understand: A Human-Centered Evaluation Framework for Explainability Methods

Julien Colin, Thomas FEL, Remi Cadene, Thomas Serre

Anytime-Valid Inference For Multinomial Count Data

Michael Lindon, Alan Malek

Semi-Supervised Semantic Segmentation via Gentle Teaching Assistant

Ying Jin, Jiaqi Wang, Dahua Lin

Generalization Bounds for Stochastic Gradient Descent via Localized ε-Covers

Sejun Park, Umut Simsekli, Murat A Erdogdu

Lazy and Fast Greedy MAP Inference for Determinantal Point Process

Shinichi Hemmi, Taihei Oki, Shinsaku Sakaue, Kaito Fujii, Satoru Iwata

Training and Inference on Any-Order Autoregressive Models the Right Way

Andy Shih, Dorsa Sadigh, Stefano Ermon

Riemannian Diffusion Models

Chin-Wei Huang, Milad Aghajohari, Joey Bose, Prakash Panangaden, Aaron C. Courville

Enhanced Meta Reinforcement Learning via Demonstrations in Sparse Reward Environments

Desik Rengarajan, Sapana Chaudhary, Jaewon Kim, Dileep Kalathil, Srinivas Shakkottai

Using Partial Monotonicity in Submodular Maximization

Loay Mualem, Moran Feldman

Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures

Emmanuel Abbe, Samy Bengio, Elisabetta Cornacchia, Jon M. Kleinberg, Aryo Lotfi

Accelerated Linearized Laplace Approximation for Bayesian Deep Learning

Zhijie Deng, Feng Zhou, Jun Zhu

Improved Coresets for Euclidean k-Means

Vincent Cohen-Addad, Kasper Green Larsen, David Saulpic, Chris Schwiegelshohn, Omar Ali Sheikh-Omar

Uni-Perceiver-MoE: Learning Sparse Generalist Models with Conditional MoEs

Jinguo Zhu, Xizhou Zhu, Wenhai Wang, Xiaohua Wang, hongsheng Li

Sustainable Online Reinforcement Learning for Auto-bidding

Zhiyu Mou, Yusen Huo, Rongquan Bai, Mingzhou Xie, Chuan Yu

Ambiguous Images With Human Judgments for Robust Visual Event Classification

Kate Sanders, Reno Kriz, Anqi Liu, Benjamin Van Durme

Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty

Jaehoon Oh, Sungnyun Kim, Namgyu Ho, Jin-Hwa Kim, Hwanjun Song

Towards Safe Reinforcement Learning with a Safety Editor Policy

Haonan Yu, Wei Xu, Haichao Zhang

Concept Activation Regions: A Generalized Framework For Concept-Based Explanations

Jonathan Crabbe, Mihaela van der Schaar

Planning for Sample Efficient Imitation Learning

Zhao-Heng Yin, Weirui Ye, Qifeng Chen, Yang Gao

Implicit Neural Representations with Levels-of-Experts

Zekun Hao, Arun Mallya, Serge Belongie, Ming-Yu Liu

Molecule Generation by Principal Subgraph Mining and Assembling

Xiangzhe Kong, Wenbing Huang, Zhixing Tan, Yang Liu

The Phenomenon of Policy Churn

Tom Schaul, Andre Barreto, John Quan, Georg Ostrovski

Few-Shot Audio-Visual Learning of Environment Acoustics

Sagnik Majumder, Changan Chen, Ziad Al-Halah, Kristen Grauman

Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering

Pan Lu, Swaroop Mishra, Tanglin Xia, Liang Qiu, Kai-Wei Chang

Obj2Seq: Formatting Objects as Sequences with Class Prompt for Visual Tasks

Zhiyang Chen, Yousong Zhu, Zhaowen Li, Fan Yang, Wei Li

A Reduction to Binary Approach for Debiasing Multiclass Datasets

Ibrahim M Alabdulmohsin, Jessica Schrouff, Sanmi Koyejo

Open-Ended Reinforcement Learning with Neural Reward Functions

Robert Meier, Asier Mujika

The Minority Matters: A Diversity-Promoting Collaborative Metric Learning Algorithm

Shilong Bao, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao

Free Probability for predicting the performance of feed-forward fully connected neural networks

Reda CHHAIBI, Tariq Daouda, Ezechiel Kahn

Intra-agent speech permits zero-shot task acquisition

Chen Yan, Federico Carnevale, Petko I Georgiev, Adam Santoro, Aurelia Guy

Riemannian Score-Based Generative Modelling

Valentin De Bortoli, Emile Mathieu, Michael Hutchinson, James Thornton, Yee Whye Teh

Semi-Supervised Learning with Decision Trees: Graph Laplacian Tree Alternating Optimization

Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán

Seeing the forest and the tree: Building representations of both individual and collective dynamics with transformers

Ran Liu, Mehdi Azabou, Max Dabagia, Jingyun Xiao, Eva Dyer

A Causal Analysis of Harm

Sander Beckers, Hana Chockler, Joseph Halpern

Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation

Zhouxing Shi, Yihan Wang, Huan Zhang, J. Zico Kolter, Cho-jui Hsieh

Why neural networks find simple solutions: The many regularizers of geometric complexity

Benoit Dherin, Michael Munn, Mihaela Rosca, David Barrett

DevFly: Bio-Inspired Development of Binary Connections for Locality Preserving Sparse Codes

Tianqi Wei, Rana Alkhoury Maroun, Qinghai Guo, Barbara Webb

Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees

Andrea Tirinzoni, Matteo Papini, Ahmed Touati, Alessandro Lazaric, Matteo Pirotta

HumanLiker: A Human-like Object Detector to Model the Manual Labeling Process

Ping Guo, Yangguang Zhu, Chenglong Liu, Peng Wang, Hao-Ran Wei

Kyle Luther, Sebastian Seung

Not too little, not too much: a theoretical analysis of graph (over)smoothing

Nicolas Keriven

Monte Carlo Augmented Actor-Critic for Sparse Reward Deep Reinforcement Learning from Suboptimal Demonstrations

Albert Wilcox, Ashwin Balakrishna, Jules Dedieu, Wyame Benslimane, Daniel Brown

Learning to Accelerate Partial Differential Equations via Latent Global Evolution

Tailin Wu, Takashi Maruyama, Jure Leskovec

Scalable Infomin Learning

Yanzhi Chen, weihao sun, Yingzhen Li, Adrian Weller

GAPX: Generalized Autoregressive Paraphrase-Identification X

Yifei Zhou, Renyu Li, Hayden Housen, Ser Nam Lim

CoNT: Contrastive Neural Text Generation

Chenxin An, Jiangtao Feng, Kai Lv, Lingpeng Kong, Xipeng Qiu

Towards Understanding the Condensation of Neural Networks at Initial Training

Hanxu Zhou, Zhou Qixuan, Tao Luo, Yaoyu Zhang, Zhi-Qin Xu

What You See is What You Get: Principled Deep Learning via Distributional Generalization

Bogdan Kulynych, Yao-Yuan Yang, Yaodong Yu, Jarosław Błasiok, Preetum Nakkiran

Masked Generative Adversarial Networks are Data-Efficient Generation Learners

Jiaxing Huang, Kaiwen Cui, Dayan Guan, Aoran Xiao, Fangneng Zhan

Incrementality Bidding via Reinforcement Learning under Mixed and Delayed Rewards

Ashwinkumar Badanidiyuru Varadaraja, Zhe Feng, Tianxi Li, Haifeng Xu

Unsupervised Multi-Object Segmentation by Predicting Probable Motion Patterns

Laurynas Karazija, Subhabrata Choudhury, Iro Laina, Christian Rupprecht, Andrea Vedaldi

Augmenting Online Algorithms with ε-Accurate Predictions

Anupam Gupta, Debmalya Panigrahi, Bernardo Subercaseaux, Kevin Sun

PopArt: Efficient Sparse Regression and Experimental Design for Optimal Sparse Linear Bandits

Kyoungseok Jang, Chicheng Zhang, Kwang-Sung Jun

VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely?

Jiawei Jiang, Lukas Burkhalter, Fangcheng Fu, Bolin Ding, Bo Du

CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label Classification

Siddhant Kharbanda, Atmadeep Banerjee, Erik Schultheis, Rohit Babbar

GOOD: A Graph Out-of-Distribution Benchmark

Shurui Gui, Xiner Li, Limei Wang, Shuiwang Ji

Causality Preserving Chaotic Transformation and Classification using Neurochaos Learning

Harikrishnan N B, Aditi Kathpalia, Nithin Nagaraj

MoGDE: Boosting Mobile Monocular 3D Object Detection with Ground Depth Estimation

Yunsong Zhou, Quan Liu, Hongzi Zhu, Yunzhe Li, Shan Chang

Maximizing and Satisficing in Multi-armed Bandits with Graph Information

Parth Thaker, Mohit Malu, Nikhil Rao, Gautam Dasarathy

Deep Differentiable Logic Gate Networks

Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen

DeepInteraction: 3D Object Detection via Modality Interaction

Zeyu Yang, Jiaqi Chen, Zhenwei Miao, Wei Li, Xiatian Zhu

On the Epistemic Limits of Personalized Prediction

Lucas Monteiro Paes, Carol Long, Berk Ustun, Flavio Calmon

HF-NeuS: Improved Surface Reconstruction Using High-Frequency Details

Yiqun Wang, Ivan Skorokhodov, Peter Wonka

Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning

Haokun Liu, Derek Tam, Mohammed Muqeeth, Jay Mohta, Tenghao Huang

Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization

Minsu Kim, Junyoung Park, Jinkyoo Park

On the Global Convergence Rates of Decentralized Softmax Gradient Play in Markov Potential Games

Runyu Zhang, Jincheng Mei, Bo Dai, Dale Schuurmans, Na Li

Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative

Tianxin Wei, Yuning You, Tianlong Chen, Yang Shen, Jingrui He

The Unreasonable Effectiveness of Fully-Connected Layers for Low-Data Regimes

Peter Kocsis, Peter Súkeník, Guillem Braso, Matthias Niessner, Laura Leal-Taixé

Best of Both Worlds Model Selection

Aldo Pacchiano, Christoph Dann, Claudio Gentile

M$^4$I: Multi-modal Models Membership Inference

Pingyi Hu, Zihan Wang, Ruoxi Sun, Hu Wang, Minhui Xue

TempEL: Linking Dynamically Evolving and Newly Emerging Entities

Klim Zaporojets, Lucie-Aimée Kaffee, Johannes Deleu, Thomas Demeester, Chris Develder