NeurIPS 2022 Tuesday 11/29

Timezone: America/Chicago

Full Schedule Mon 11/28 Tue 11/29 Wed 11/30 Thu 12/1 Fri 12/2 Sat 12/3 Sun 12/4 Mon 12/5 Tue 12/6 Wed 12/7 Thu 12/8 Fri 12/9

Registration Desk

7:00 AM - 6:00 PM

Invited Talk

Algorithms On the Bench: Examining Validity of ML Systems in the Public Sphere

Rediet Abebe

9:30 AM - 10:30 AM

Poster

Poster Session 1

11:00 AM - 1:00 PM

409 Events in this session

Efficient Change-Point Detection for Tackling Piecewise-Stationary Bandits

Lilian Besson · Emilie Kaufmann · Odalric-Ambrym Maillard · Julien Seznec

A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking

Keyu Duan · Zirui Liu · Peihao Wang · Wenqing Zheng · Kaixiong Zhou · Tianlong Chen · Xia Hu · Zhangyang Wang

FedPop: A Bayesian Approach for Personalised Federated Learning

Nikita Kotelevskii · Maxime Vono · Alain Durmus · Eric Moulines

Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach

Kaiwen Yang · Yanchao Sun · Jiahao Su · Fengxiang He · Xinmei Tian · Furong Huang · Tianyi Zhou · Dacheng Tao

Functional Ensemble Distillation

Coby Penso · Idan Achituve · Ethan Fetaya

Improving Zero-Shot Generalization in Offline Reinforcement Learning using Generalized Similarity Functions

Bogdan Mazoure · Ilya Kostrikov · Ofir Nachum · Jonathan Tompson

Differentially Private Model Compression

FatemehSadat Mireshghallah · Arturs Backurs · Huseyin A. Inan · Lukas Wutschitz · Janardhan Kulkarni

Self-explaining deep models with logic rule reasoning

Seungeon Lee · Xiting Wang · Sungwon Han · Xiaoyuan Yi · Xing Xie · Meeyoung Cha

AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking Keypoints

Xingzhe He · Bastian Wandt · Helge Rhodin

Behavior Transformers: Cloning $k$ modes with one stone

Nur Muhammad Shafiullah · Zichen Cui · Ariuntuya (Arty) Altanzaya · Lerrel Pinto

Equivariant Networks for Zero-Shot Coordination

Darius Muglich · Christian Schroeder de Witt · Elise van der Pol · Shimon Whiteson · Jakob Foerster

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

Hui Yuan · Chengzhuo Ni · Huazheng Wang · Xuezhou Zhang · Le Cong · Csaba Szepesvari · Mengdi Wang

What You See is What You Classify: Black Box Attributions

Steven Stalder · Nathanael Perraudin · Radhakrishna Achanta · Fernando Perez-Cruz · Michele Volpi

Active Surrogate Estimators: An Active Learning Approach to Label-Efficient Model Evaluation

Jannik Kossen · Sebastian Farquhar · Yarin Gal · Thomas Rainforth

Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces

Alexander Thebelt · Calvin Tsay · Robert Lee · Nathan Sudermann-Merx · David Walz · Behrang Shafei · Ruth Misener

Sparse Fourier Backpropagation in Cryo-EM Reconstruction

Dari Kimanius · Kiarash Jamali · Sjors Scheres

Predictive Querying for Autoregressive Neural Sequence Models

Alex Boyd · Samuel Showalter · Stephan Mandt · Padhraic Smyth

Extracting computational mechanisms from neural data using low-rank RNNs

Adrian Valente · Jonathan Pillow · Srdjan Ostojic

Modeling the Machine Learning Multiverse

Samuel J. Bell · Onno Kampman · Jesse Dodge · Neil Lawrence

AUTOMATA: Gradient Based Data Subset Selection for Compute-Efficient Hyper-parameter Tuning

Krishnateja Killamsetty · Guttu Sai Abhishek · Aakriti Lnu · Ganesh Ramakrishnan · Alexandre Evfimievski · Lucian Popa · Rishabh Iyer

Retrospective Adversarial Replay for Continual Learning

Lilly Kumari · Shengjie Wang · Tianyi Zhou · Jeff A Bilmes

Learning Neural Set Functions Under the Optimal Subset Oracle

Zijing Ou · Tingyang Xu · Qinliang Su · Yingzhen Li · Peilin Zhao · Yatao Bian

Efficient Architecture Search for Diverse Tasks

Junhong Shen · Misha Khodak · Ameet Talwalkar

When Do Flat Minima Optimizers Work?

Jean Kaddour · Linqing Liu · Ricardo Silva · Matt Kusner

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

Peter Kocsis · Peter Súkeník · Guillem Braso · Matthias Niessner · Laura Leal-Taixé · Ismail Elezi

LTMD: Learning Improvement of Spiking Neural Networks with Learnable Thresholding Neurons and Moderate Dropout

SIQI WANG · Tee Hiang Cheng · Meng-Hiot Lim

Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation

Shiqi Yang · yaxing wang · kai wang · Shangling Jui · Joost van de Weijer

UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup

Zongbo Han · Zhipeng Liang · Fan Yang · Liu Liu · Lanqing Li · Yatao Bian · Peilin Zhao · Bingzhe Wu · Changqing Zhang · Jianhua Yao

Scalable Multi-agent Covering Option Discovery based on Kronecker Graphs

Jiayu Chen · Jingdi Chen · Tian Lan · Vaneet Aggarwal

PaCo: Parameter-Compositional Multi-task Reinforcement Learning

Lingfeng Sun · Haichao Zhang · Wei Xu · Masayoshi TOMIZUKA

ConfounderGAN: Protecting Image Data Privacy with Causal Confounder

Qi Tian · Kun Kuang · Kelu Jiang · Furui Liu · Zhihua Wang · Fei Wu

Mask-based Latent Reconstruction for Reinforcement Learning

Tao Yu · Zhizheng Zhang · Cuiling Lan · Yan Lu · Zhibo Chen

Improved Fine-Tuning by Better Leveraging Pre-Training Data

Ziquan Liu · Yi Xu · Yuanhong Xu · Qi Qian · Hao Li · Xiangyang Ji · Antoni Chan · Rong Jin

Redundancy-Free Message Passing for Graph Neural Networks

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

Towards Improving Faithfulness in Abstractive Summarization

Xiuying Chen · Mingzhe Li · Xin Gao · Xiangliang Zhang

Delving into Out-of-Distribution Detection with Vision-Language Representations

Yifei Ming · Ziyang Cai · Jiuxiang Gu · Yiyou Sun · Wei Li · Yixuan Li

CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning

Hung Le · Yue Wang · Akhilesh Deepak Gotmare · Silvio Savarese · Steven Chu Hong Hoi

Layer Freezing & Data Sieving: Missing Pieces of a Generic Framework for Sparse Training

Geng Yuan · Yanyu Li · Sheng Li · Zhenglun Kong · Sergey Tulyakov · Xulong Tang · Yanzhi Wang · Jian Ren

EfficientFormer: Vision Transformers at MobileNet Speed

Yanyu Li · Geng Yuan · Yang Wen · Ju Hu · Georgios Evangelidis · Sergey Tulyakov · Yanzhi Wang · Jian Ren

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

Zhan Tong · Yibing Song · Jue Wang · Limin Wang

Large-batch Optimization for Dense Visual Predictions: Training Faster R-CNN in 4.2 Minutes

Zeyue Xue · Jianming Liang · Guanglu Song · Zhuofan Zong · Liang Chen · Yu Liu · Ping Luo

Semi-Supervised Video Salient Object Detection Based on Uncertainty-Guided Pseudo Labels

Yongri Piao · Chenyang Lu · Miao Zhang · Huchuan Lu

UniCLIP: Unified Framework for Contrastive Language-Image Pre-training

Janghyeon Lee · Jongsuk Kim · Hyounguk Shon · Bumsoo Kim · Seung Hwan Kim · Honglak Lee · Junmo Kim

Controllable 3D Face Synthesis with Conditional Generative Occupancy Fields

Keqiang Sun · Shangzhe Wu · Zhaoyang Huang · Ning Zhang · Quan Wang · Hongsheng Li

Learning Consistency-Aware Unsigned Distance Functions Progressively from Raw Point Clouds

Junsheng Zhou · Baorui Ma · Yu-Shen Liu · Yi Fang · Zhizhong Han

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 · Se-Young Yun

Okapi: Generalising Better by Making Statistical Matches Match

Myles Bartlett · Sara Romiti · Viktoriia Sharmanska · Novi Quadrianto

Revisiting Sparse Convolutional Model for Visual Recognition

xili dai · Mingyang Li · Pengyuan Zhai · Shengbang Tong · Xingjian Gao · Shao-Lun Huang · Zhihui Zhu · Chong You · Yi Ma

Random Normalization Aggregation for Adversarial Defense

Minjing Dong · Xinghao Chen · Yunhe Wang · Chang Xu

Batch Multi-Fidelity Active Learning with Budget Constraints

Shibo Li · Jeff M Phillips · Xin Yu · Robert Kirby · Shandian Zhe

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

Zhiqi Bu · Jialin Mao · Shiyun Xu

Factuality Enhanced Language Models for Open-Ended Text Generation

Nayeon Lee · Wei Ping · Peng Xu · Mostofa Patwary · Pascale N Fung · Mohammad Shoeybi · Bryan Catanzaro

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

Pan Lu · Swaroop Mishra · Tanglin Xia · Liang Qiu · Kai-Wei Chang · Song-Chun Zhu · Oyvind Tafjord · Peter Clark · Ashwin Kalyan

A Closer Look at Weakly-Supervised Audio-Visual Source Localization

Shentong Mo · Pedro Morgado

GlanceNets: Interpretable, Leak-proof Concept-based Models

Emanuele Marconato · Andrea Passerini · Stefano Teso

AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment of Implicit Graph Generators

Wenkai Xu · Gesine D Reinert

No Free Lunch from Deep Learning in Neuroscience: A Case Study through Models of the Entorhinal-Hippocampal Circuit

Rylan Schaeffer · Mikail Khona · Ila Fiete

Inherently Explainable Reinforcement Learning in Natural Language

Xiangyu Peng · Mark Riedl · Prithviraj Ammanabrolu

EZNAS: Evolving Zero-Cost Proxies For Neural Architecture Scoring

Yash Akhauri · Juan Munoz · Nilesh Jain · Ravishankar Iyer

Uncertainty Estimation Using Riemannian Model Dynamics for Offline Reinforcement Learning

Guy Tennenholtz · Shie Mannor

Structured Energy Network As a Loss

Jay Yoon Lee · Dhruvesh Patel · Purujit Goyal · Wenlong Zhao · Zhiyang Xu · Andrew McCallum

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

Shilong Bao · Qianqian Xu · Zhiyong Yang · Yuan He · Xiaochun Cao · Qingming Huang

Sharpness-Aware Training for Free

JIAWEI DU · Daquan Zhou · Jiashi Feng · Vincent Tan · Joey Tianyi Zhou

Interpreting Operation Selection in Differentiable Architecture Search: A Perspective from Influence-Directed Explanations

Miao Zhang · Wei Huang · Bin Yang

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

Samarth Gupta · Saurabh Amin

Amortized Mixing Coupling Processes for Clustering

Huafeng Liu · Liping Jing

GraphQNTK: Quantum Neural Tangent Kernel for Graph Data

Yehui Tang · Junchi Yan

ShuffleMixer: An Efficient ConvNet for Image Super-Resolution

Long Sun · Jinshan Pan · Jinhui Tang

Quo Vadis: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking?

Patrick Dendorfer · Vladimir Yugay · Aljosa Osep · Laura Leal-Taixé

Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking Consistency

Viraj Prabhu · Sriram Yenamandra · Aaditya Singh · Judy Hoffman

Learning Latent Seasonal-Trend Representations for Time Series Forecasting

Zhiyuan Wang · Xovee Xu · Weifeng Zhang · Goce Trajcevski · Ting Zhong · Fan Zhou

Pluralistic Image Completion with Gaussian Mixture Models

Xiaobo Xia · Wenhao Yang · Jie Ren · Yewen Li · Yibing Zhan · Bo Han · Tongliang Liu

CoupAlign: Coupling Word-Pixel with Sentence-Mask Alignments for Referring Image Segmentation

Zicheng Zhang · Yi Zhu · Jianzhuang Liu · Xiaodan Liang · Wei Ke

Make an Omelette with Breaking Eggs: Zero-Shot Learning for Novel Attribute Synthesis

Yu-Hsuan Li · Tzu-Yin Chao · Ching-Chun Huang · Pin-Yu Chen · Wei-Chen Chiu

Graph Few-shot Learning with Task-specific Structures

Song Wang · Chen Chen · Jundong Li

Co-Modality Graph Contrastive Learning for Imbalanced Node Classification

Yiyue Qian · Chunhui Zhang · Yiming Zhang · Qianlong Wen · Yanfang Ye · Chuxu Zhang

Recommender Forest for Efficient Retrieval

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

Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting

Chengyu Dong · Liyuan Liu · Jingbo Shang

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

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

SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training

Enmao Diao · Jie Ding · Vahid Tarokh

Task-Agnostic Graph Explanations

Yaochen Xie · Sumeet Katariya · Xianfeng Tang · Edward Huang · Nikhil Rao · Karthik Subbian · Shuiwang Ji

CageNeRF: Cage-based Neural Radiance Field for Generalized 3D Deformation and Animation

Yicong Peng · Yichao Yan · Shengqi Liu · Yuhao Cheng · Shanyan Guan · Bowen Pan · Guangtao Zhai · Xiaokang Yang

LECO: Learnable Episodic Count for Task-Specific Intrinsic Reward

Daejin Jo · Sungwoong Kim · Daniel Nam · Taehwan Kwon · Seungeun Rho · Jongmin Kim · Donghoon Lee

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

Yiqun Mei · Pengfei Guo · Mo Zhou · Vishal Patel

Block-Recurrent Transformers

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

Distinguishing Learning Rules with Brain Machine Interfaces

Jacob Portes · Christian Schmid · James M Murray

Imitating Past Successes can be Very Suboptimal

Benjamin Eysenbach · Soumith Udatha · Russ Salakhutdinov · Sergey Levine

Bounded-Regret MPC via Perturbation Analysis: Prediction Error, Constraints, and Nonlinearity

Yiheng Lin · Yang Hu · Guannan Qu · Tongxin Li · Adam Wierman

Neural Conservation Laws: A Divergence-Free Perspective

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

Relaxing Equivariance Constraints with Non-stationary Continuous Filters

Tycho van der Ouderaa · David W. Romero · Mark van der Wilk

Continual Learning In Environments With Polynomial Mixing Times

Matthew Riemer · Sharath Chandra Raparthy · Ignacio Cases · Gopeshh Subbaraj · Maximilian Puelma Touzel · Irina Rish

Non-Linear Coordination Graphs

Yipeng Kang · Tonghan Wang · Qianlan Yang · Xiaoran Wu · Chongjie Zhang

Rate-Distortion Theoretic Bounds on Generalization Error for Distributed Learning

Milad Sefidgaran · Romain Chor · Abdellatif Zaidi

Mirror Descent Maximizes Generalized Margin and Can Be Implemented Efficiently

Haoyuan Sun · Kwangjun Ahn · Christos Thrampoulidis · Navid Azizan

Instance-Dependent Near-Optimal Policy Identification in Linear MDPs via Online Experiment Design

Andrew Wagenmaker · Kevin Jamieson

On the Complexity of Adversarial Decision Making

Dylan J Foster · Alexander Rakhlin · Ayush Sekhari · Karthik Sridharan

Convergence beyond the over-parameterized regime using Rayleigh quotients

David A. R. Robin · Kevin Scaman · marc lelarge

An Algorithm for Learning Switched Linear Dynamics from Data

Guillaume Berger · Monal Narasimhamurthy · Kandai Watanabe · Morteza Lahijanian · Sriram Sankaranarayanan

Differentially Private Learning Needs Hidden State (Or Much Faster Convergence)

Jiayuan Ye · Reza Shokri

Cluster Randomized Designs for One-Sided Bipartite Experiments

Jennifer Brennan · Vahab Mirrokni · Jean Pouget-Abadie

Near-Optimal Randomized Exploration for Tabular Markov Decision Processes

Zhihan Xiong · Ruoqi Shen · Qiwen Cui · Maryam Fazel · Simon Du

Order-Invariant Cardinality Estimators Are Differentially Private

Charlie Dickens · Justin Thaler · Daniel Ting

Mirror Descent with Relative Smoothness in Measure Spaces, with application to Sinkhorn and EM

Pierre-Cyril Aubin-Frankowski · Anna Korba · Flavien Léger

Generalization Error Bounds on Deep Learning with Markov Datasets

Lan V. Truong

Autoinverse: Uncertainty Aware Inversion of Neural Networks

Navid Ansari · Hans-peter Seidel · Nima Vahidi Ferdowsi · Vahid Babaei

Optimal Transport of Classifiers to Fairness

Maarten Buyl · Tijl De Bie

Path Independent Equilibrium Models Can Better Exploit Test-Time Computation

Cem Anil · Ashwini Pokle · Kaiqu Liang · Johannes Treutlein · Yuhuai Wu · Shaojie Bai · J. Zico Kolter · Roger Grosse

Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting

Prasanna Sattigeri · Soumya Ghosh · Inkit Padhi · Pierre Dognin · Kush Varshney

On Sample Optimality in Personalized Collaborative and Federated Learning

Mathieu Even · Laurent Massoulié · Kevin Scaman

Active Ranking without Strong Stochastic Transitivity

Hao Lou · Tao Jin · Yue Wu · Pan Xu · Quanquan Gu · Farzad Farnoud

How Sampling Impacts the Robustness of Stochastic Neural Networks

Sina Däubener · Asja Fischer

Convexity Certificates from Hessians

Julien Klaus · Niklas Merk · Konstantin Wiedom · Sören Laue · Joachim Giesen

Optimal Binary Classification Beyond Accuracy

Shashank Singh · Justin Khim

Sample Constrained Treatment Effect Estimation

Raghavendra Addanki · David Arbour · Tung Mai · Cameron Musco · Anup Rao

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

Jason Altschuler · Kunal Talwar

SecureFedYJ: a safe feature Gaussianization protocol for Federated Learning

Tanguy Marchand · Boris Muzellec · Constance Béguier · Jean Ogier du Terrail · Mathieu Andreux

Continual learning: a feature extraction formalization, an efficient algorithm, and fundamental obstructions

Binghui Peng · Andrej Risteski

Evolution of Neural Tangent Kernels under Benign and Adversarial Training

Noel Loo · Ramin Hasani · Alexander Amini · Daniela Rus

Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference

Jasper Tan · Blake Mason · Hamid Javadi · Richard Baraniuk

Active Exploration for Inverse Reinforcement Learning

David Lindner · Andreas Krause · Giorgia Ramponi

A Unified Framework for Deep Symbolic Regression

Mikel Landajuela · Chak Shing Lee · Jiachen Yang · Ruben Glatt · Claudio P Santiago · Ignacio Aravena · Terrell Mundhenk · Garrett Mulcahy · Brenden K Petersen

Learning Generalized Policy Automata for Relational Stochastic Shortest Path Problems

Rushang Karia · Rashmeet Kaur Nayyar · Siddharth Srivastava

CARD: Classification and Regression Diffusion Models

Xizewen Han · Huangjie Zheng · Mingyuan Zhou

GT-GAN: General Purpose Time Series Synthesis with Generative Adversarial Networks

Jinsung Jeon · JEONGHAK KIM · Haryong Song · Seunghyeon Cho · Noseong Park

So3krates: Equivariant attention for interactions on arbitrary length-scales in molecular systems

Thorben Frank · Oliver Unke · Klaus-Robert Müller

Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders

Kiarash Zahirnia · Oliver Schulte · Parmis Naddaf · Ke Li

Learning Representations via a Robust Behavioral Metric for Deep Reinforcement Learning

Jianda Chen · Sinno Pan

Transferring Fairness under Distribution Shifts via Fair Consistency Regularization

Bang An · Zora Che · Mucong Ding · Furong Huang

Bridging the Gap from Asymmetry Tricks to Decorrelation Principles in Non-contrastive Self-supervised Learning

Kang-Jun Liu · Masanori Suganuma · Takayuki Okatani

Template based Graph Neural Network with Optimal Transport Distances

Cédric Vincent-Cuaz · Rémi Flamary · Marco Corneli · Titouan Vayer · Nicolas Courty

A composable machine-learning approach for steady-state simulations on high-resolution grids

Rishikesh Ranade · Chris Hill · Lalit Ghule · Jay Pathak

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

Zhize Li · Haoyu Zhao · Boyue Li · Yuejie Chi

A Unified Analysis of Mixed Sample Data Augmentation: A Loss Function Perspective

Chanwoo Park · Sangdoo Yun · Sanghyuk Chun

From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent

Christopher De Sa · Satyen Kale · Jason Lee · Ayush Sekhari · Karthik Sridharan

Stability and Generalization for Markov Chain Stochastic Gradient Methods

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

Learning Energy Networks with Generalized Fenchel-Young Losses

Mathieu Blondel · Felipe Llinares-Lopez · Robert Dadashi · Leonard Hussenot · Matthieu Geist

AZ-whiteness test: a test for signal uncorrelation on spatio-temporal graphs

Daniele Zambon · Cesare Alippi

Equivariant Networks for Crystal Structures

Oumar Kaba · Siamak Ravanbakhsh

Text Classification with Born's Rule

Emanuele Guidotti · Alfio Ferrara

A Probabilistic Graph Coupling View of Dimension Reduction

Hugues Van Assel · Thibault Espinasse · Julien Chiquet · Franck Picard

Laplacian Autoencoders for Learning Stochastic Representations

Marco Miani · Frederik Warburg · Pablo Moreno-Muñoz · Nicki Skafte · Søren Hauberg

UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs

Philipp Oberdiek · Gernot Fink · Matthias Rottmann

Variational Model Perturbation for Source-Free Domain Adaptation

Mengmeng Jing · Xiantong Zhen · Jingjing Li · Cees Snoek

On the Effect of Pre-training for Transformer in Different Modality on Offline Reinforcement Learning

Shiro Takagi

Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Maps

Yue Hu · Shaoheng Fang · Zixing Lei · Yiqi Zhong · Siheng Chen

EcoFormer: Energy-Saving Attention with Linear Complexity

Jing Liu · Zizheng Pan · Haoyu He · Jianfei Cai · Bohan Zhuang

Dataset Distillation using Neural Feature Regression

Yongchao Zhou · Ehsan Nezhadarya · Jimmy Ba

Iterative Scene Graph Generation

Siddhesh Khandelwal · Leonid Sigal

ALIFE: Adaptive Logit Regularizer and Feature Replay for Incremental Semantic Segmentation

Youngmin Oh · Donghyeon Baek · Bumsub Ham

Hyperbolic Feature Augmentation via Distribution Estimation and Infinite Sampling on Manifolds

Zhi Gao · Yuwei Wu · Yunde Jia · Mehrtash Harandi

Provably Adversarially Robust Detection of Out-of-Distribution Data (Almost) for Free

Alexander Meinke · Julian Bitterwolf · Matthias Hein

Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees

Aleksandr Beznosikov · Peter Richtarik · Michael Diskin · Max Ryabinin · Alexander Gasnikov

Global Convergence and Stability of Stochastic Gradient Descent

Vivak Patel · Shushu Zhang · Bowen Tian

Regret Bounds for Information-Directed Reinforcement Learning

Botao Hao · Tor Lattimore

Truncated Matrix Power Iteration for Differentiable DAG Learning

Zhen Zhang · Ignavier Ng · Dong Gong · Yuhang Liu · Ehsan Abbasnejad · Mingming Gong · Kun Zhang · Javen Qinfeng Shi

Error Analysis of Tensor-Train Cross Approximation

Zhen Qin · Alexander Lidiak · Zhexuan Gong · Gongguo Tang · Michael B Wakin · Zhihui Zhu

Efficient Risk-Averse Reinforcement Learning

Ido Greenberg · Yinlam Chow · Mohammad Ghavamzadeh · Shie Mannor

Learning Robust Dynamics through Variational Sparse Gating

Arnav Kumar Jain · Shivakanth Sujit · Shruti Joshi · Vincent Michalski · Danijar Hafner · Samira Ebrahimi Kahou

DiSC: Differential Spectral Clustering of Features

Ram Dyuthi Sristi · Gal Mishne · Ariel Jaffe

WeightedSHAP: analyzing and improving Shapley based feature attributions

Yongchan Kwon · James Zou

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

Emmanuel Abbe · Samy Bengio · Elisabetta Cornacchia · Jon Kleinberg · Aryo Lotfi · Maithra Raghu · Chiyuan Zhang

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

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

Safety Guarantees for Neural Network Dynamic Systems via Stochastic Barrier Functions

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

A Unified Framework for Alternating Offline Model Training and Policy Learning

Shentao Yang · Shujian Zhang · Yihao Feng · Mingyuan Zhou

Decentralized Local Stochastic Extra-Gradient for Variational Inequalities

Aleksandr Beznosikov · Pavel Dvurechenskii · Anastasiia Koloskova · Valentin Samokhin · Sebastian Stich · Alexander Gasnikov

Gradient Estimation with Discrete Stein Operators

Jiaxin Shi · Yuhao Zhou · Jessica Hwang · Michalis Titsias · Lester Mackey

On the SDEs and Scaling Rules for Adaptive Gradient Algorithms

Sadhika Malladi · Kaifeng Lyu · Abhishek Panigrahi · Sanjeev Arora

Root Cause Analysis of Failures in Microservices through Causal Discovery

Azam Ikram · Sarthak Chakraborty · Subrata Mitra · Shiv Saini · Saurabh Bagchi · Murat Kocaoglu

Low-rank Optimal Transport: Approximation, Statistics and Debiasing

Meyer Scetbon · Marco Cuturi

Learning single-index models with shallow neural networks

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

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

Veit David Wild · Robert Hu · Dino Sejdinovic

Efficient identification of informative features in simulation-based inference

Jonas Beck · Michael Deistler · Yves Bernaerts · Jakob H Macke · Philipp Berens

Exact learning dynamics of deep linear networks with prior knowledge

Lukas Braun · Clémentine Dominé · James Fitzgerald · Andrew Saxe

Adversarial training for high-stakes reliability

Daniel Ziegler · Seraphina Nix · Lawrence Chan · Tim Bauman · Peter Schmidt-Nielsen · Tao Lin · Adam Scherlis · Noa Nabeshima · Benjamin Weinstein-Raun · Daniel de Haas · Buck Shlegeris · Nate Thomas

NaturalProver: Grounded Mathematical Proof Generation with Language Models

Sean Welleck · Jiacheng Liu · Ximing Lu · Hannaneh Hajishirzi · Yejin Choi

Open-Ended Reinforcement Learning with Neural Reward Functions

Robert Meier · Asier Mujika

Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs

Etienne Boursier · Loucas PILLAUD-VIVIEN · Nicolas Flammarion

Memory safe computations with XLA compiler

Artem Artemev · Yuze An · Tilman Roeder · Mark van der Wilk

C2FAR: Coarse-to-Fine Autoregressive Networks for Precise Probabilistic Forecasting

Shane Bergsma · Tim Zeyl · Javad Rahimipour Anaraki · Lei Guo

Continuous MDP Homomorphisms and Homomorphic Policy Gradient

Sahand Rezaei-Shoshtari · Rosie Zhao · Prakash Panangaden · David Meger · Doina Precup

Data augmentation for efficient learning from parametric experts

Alexandre Galashov · Josh Merel · Nicolas Heess

Generating Training Data with Language Models: Towards Zero-Shot Language Understanding

Yu Meng · Jiaxin Huang · Yu Zhang · Jiawei Han

Deep Surrogate Assisted Generation of Environments

Varun Bhatt · Bryon Tjanaka · Matthew Fontaine · Stefanos Nikolaidis

SGAM: Building a Virtual 3D World through Simultaneous Generation and Mapping

Yuan Shen · Wei-Chiu Ma · Shenlong Wang

Evaluating Latent Space Robustness and Uncertainty of EEG-ML Models under Realistic Distribution Shifts

Neeraj Wagh · Jionghao Wei · Samarth Rawal · Brent M Berry · Yogatheesan Varatharajah

Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution

Leon Hetzel · Simon Boehm · Niki Kilbertus · Stephan Günnemann · mohammad lotfollahi · Fabian Theis

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

Michiel Bakker · Martin Chadwick · Hannah Sheahan · Michael Tessler · Lucy Campbell-Gillingham · Jan Balaguer · Nat McAleese · Amelia Glaese · John Aslanides · Matt Botvinick · Christopher Summerfield

A Unified Sequence Interface for Vision Tasks

Ting Chen · Saurabh Saxena · Lala Li · Tsung-Yi Lin · David Fleet · Geoffrey Hinton

Learning Probabilistic Models from Generator Latent Spaces with Hat EBM

Mitch Hill · Erik Nijkamp · Jonathan Mitchell · Bo Pang · Song-Chun Zhu

Deep Generalized Schrödinger Bridge

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

NSNet: A General Neural Probabilistic Framework for Satisfiability Problems

Zhaoyu Li · Xujie Si

Distributionally Robust Optimization with Data Geometry

Jiashuo Liu · Jiayun Wu · Bo Li · Peng Cui

Quantifying Statistical Significance of Neural Network-based Image Segmentation by Selective Inference

Vo Nguyen Le Duy · Shogo Iwazaki · Ichiro Takeuchi

On Efficient Online Imitation Learning via Classification

Yichen Li · Chicheng Zhang

Group Meritocratic Fairness in Linear Contextual Bandits

Riccardo Grazzi · Arya Akhavan · John IF Falk · Leonardo Cella · Massimiliano Pontil

Subspace Recovery from Heterogeneous Data with Non-isotropic Noise

John Duchi · Vitaly Feldman · Lunjia Hu · Kunal Talwar

Knowledge Distillation: Bad Models Can Be Good Role Models

Gal Kaplun · Eran Malach · Preetum Nakkiran · Shai Shalev-Shwartz

Active Labeling: Streaming Stochastic Gradients

Vivien Cabannes · Francis Bach · Vianney Perchet · Alessandro Rudi

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

Stability and Generalization of Kernel Clustering: from Single Kernel to Multiple Kernel

Weixuan Liang · Xinwang Liu · Yong Liu · sihang zhou · Jun-Jie Huang · Siwei Wang · Jiyuan Liu · Yi Zhang · En Zhu

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

Gabriele Farina · Ioannis Anagnostides · Haipeng Luo · Chung-Wei Lee · Christian Kroer · Tuomas Sandholm

Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data

Abhishek Roy · Krishnakumar Balasubramanian · Saeed Ghadimi

A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits

Ilija Bogunovic · Zihan Li · Andreas Krause · Jonathan Scarlett

Global Convergence of Federated Learning for Mixed Regression

Lili Su · Jiaming Xu · Pengkun Yang

Kernel similarity matching with Hebbian networks

Kyle Luther · Sebastian Seung

Improved techniques for deterministic l2 robustness

Sahil Singla · Soheil Feizi

Matryoshka Representation Learning

Aditya Kusupati · Gantavya Bhatt · Aniket Rege · Matthew Wallingford · Aditya Sinha · Vivek Ramanujan · William Howard-Snyder · Kaifeng Chen · Sham Kakade · Prateek Jain · Ali Farhadi

Ask4Help: Learning to Leverage an Expert for Embodied Tasks

Kunal Pratap Singh · Luca Weihs · Alvaro Herrasti · Jonghyun Choi · Aniruddha Kembhavi · Roozbeh Mottaghi

Wavelet Feature Maps Compression for Image-to-Image CNNs

Shahaf E. Finder · Yair Zohav · Maor Ashkenazi · Eran Treister

Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMF

Jayneel Parekh · Sanjeel Parekh · Pavlo Mozharovskyi · Florence d'Alché-Buc · Gaël Richard

Learning Dense Object Descriptors from Multiple Views for Low-shot Category Generalization

Stefan Stojanov · Anh Thai · Zixuan Huang · James Rehg

Semantic Diffusion Network for Semantic Segmentation

Haoru Tan · Sitong Wu · Jimin Pi

Non-Linguistic Supervision for Contrastive Learning of Sentence Embeddings

Yiren Jian · Chongyang Gao · Soroush Vosoughi

CUP: Critic-Guided Policy Reuse

Jin Zhang · Siyuan Li · Chongjie Zhang

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

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

ST-Adapter: Parameter-Efficient Image-to-Video Transfer Learning

Junting Pan · Ziyi Lin · Xiatian Zhu · Jing Shao · Hongsheng Li

Distilling Representations from GAN Generator via Squeeze and Span

Yu Yang · Xiaotian Cheng · Chang Liu · Hakan Bilen · Xiangyang Ji

SHINE: SubHypergraph Inductive Neural nEtwork

Yuan Luo

Q-ViT: Accurate and Fully Quantized Low-bit Vision Transformer

Yanjing Li · Sheng Xu · Baochang Zhang · Xianbin Cao · Peng Gao · Guodong Guo

Museformer: Transformer with Fine- and Coarse-Grained Attention for Music Generation

Botao Yu · Peiling Lu · Rui Wang · Wei Hu · Xu Tan · Wei Ye · Shikun Zhang · Tao Qin · Tie-Yan Liu

LasUIE: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language Model

Hao Fei · Shengqiong Wu · Jingye Li · Bobo Li · Fei Li · Libo Qin · Meishan Zhang · Min Zhang · Tat-Seng Chua

LION: Latent Point Diffusion Models for 3D Shape Generation

xiaohui zeng · Arash Vahdat · Francis Williams · Zan Gojcic · Or Litany · Sanja Fidler · Karsten Kreis

Learning low-dimensional generalizable natural features from retina using a U-net

Siwei Wang · Benjamin Hoshal · Elizabeth de Laittre · Olivier Marre · Michael Berry · Stephanie Palmer

Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples

Maura Pintor · Luca Demetrio · Angelo Sotgiu · Ambra Demontis · Nicholas Carlini · Battista Biggio · Fabio Roli

The Pitfalls of Regularization in Off-Policy TD Learning

Gaurav Manek · J. Zico Kolter

Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees

Jue WANG · Binhang Yuan · Luka Rimanic · Yongjun He · Tri Dao · Beidi Chen · Christopher Ré · Ce Zhang

Online Training Through Time for Spiking Neural Networks

Mingqing Xiao · Qingyan Meng · Zongpeng Zhang · Di He · Zhouchen Lin

General Cutting Planes for Bound-Propagation-Based Neural Network Verification

Huan Zhang · Shiqi Wang · Kaidi Xu · Linyi Li · Bo Li · Suman Jana · Cho-Jui Hsieh · J. Zico Kolter

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

Sho Sonoda · Isao Ishikawa · Masahiro Ikeda

Single Loop Gaussian Homotopy Method for Non-convex Optimization

Hidenori Iwakiri · Yuhang Wang · Shinji Ito · Akiko Takeda

Bring Your Own Algorithm for Optimal Differentially Private Stochastic Minimax Optimization

Liang Zhang · Kiran Thekumparampil · Sewoong Oh · Niao He

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

Qiang LI · Chung-Yiu Yau · Hoi-To Wai

A Multilabel Classification Framework for Approximate Nearest Neighbor Search

Ville Hyvönen · Elias Jääsaari · Teemu Roos

Spectral Bias in Practice: The Role of Function Frequency in Generalization

Sara Fridovich-Keil · Raphael Gontijo Lopes · Rebecca Roelofs

Influencing Long-Term Behavior in Multiagent Reinforcement Learning

Dong-Ki Kim · Matthew Riemer · Miao Liu · Jakob Foerster · Michael Everett · Chuangchuang Sun · Gerald Tesauro · Jonathan How

Quality Not Quantity: On the Interaction between Dataset Design and Robustness of CLIP

Thao Nguyen · Gabriel Ilharco · Mitchell Wortsman · Sewoong Oh · Ludwig Schmidt

Giving Feedback on Interactive Student Programs with Meta-Exploration

Evan Liu · Moritz Stephan · Allen Nie · Chris Piech · Emma Brunskill · Chelsea Finn

Unsupervised Object Representation Learning using Translation and Rotation Group Equivariant VAE

Alireza Nasiri · Tristan Bepler

Few-Shot Continual Active Learning by a Robot

Ali Ayub · Carter Fendley

Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data

Allen Nie · Yannis Flet-Berliac · Deon Jordan · William Steenbergen · Emma Brunskill

VoiceBlock: Privacy through Real-Time Adversarial Attacks with Audio-to-Audio Models

Patrick O'Reilly · Andreas Bugler · Keshav Bhandari · Max Morrison · Bryan Pardo

Retrieval-Augmented Diffusion Models

Andreas Blattmann · Robin Rombach · Kaan Oktay · Jonas Müller · Björn Ommer

On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models

Kamil Deja · Anna Kuzina · Tomasz Trzcinski · Jakub Tomczak

Toward Robust Spiking Neural Network Against Adversarial Perturbation

LING LIANG · Kaidi Xu · Xing Hu · Lei Deng · Yuan Xie

Debiased Causal Tree: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding

Caizhi Tang · Huiyuan Wang · Xinyu Li · Qing Cui · Ya-Lin Zhang · Feng Zhu · Longfei Li · Jun Zhou · Linbo Jiang

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

Shiji Zhou · Wenpeng Zhang · Jiyan Jiang · Wenliang Zhong · Jinjie GU · Wenwu Zhu

Video-based Human-Object Interaction Detection from Tubelet Tokens

Danyang Tu · Wei Sun · Xiongkuo Min · Guangtao Zhai · Wei Shen

OTKGE: Multi-modal Knowledge Graph Embeddings via Optimal Transport

Zongsheng Cao · Qianqian Xu · Zhiyong Yang · Yuan He · Xiaochun Cao · Qingming Huang

Hierarchical Lattice Layer for Partially Monotone Neural Networks

Hiroki Yanagisawa · Kohei Miyaguchi · Takayuki Katsuki

On the symmetries of the synchronization problem in Cryo-EM: Multi-Frequency Vector Diffusion Maps on the Projective Plane

Gabriele Cesa · Arash Behboodi · Taco Cohen · Max Welling

What Makes a "Good" Data Augmentation in Knowledge Distillation - A Statistical Perspective

Huan Wang · Suhas Lohit · Michael Jones · Yun Fu

HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions

Yongming Rao · Wenliang Zhao · Yansong Tang · Jie Zhou · Ser Nam Lim · Jiwen Lu

Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks

Sizhe Chen · Zhehao Huang · Qinghua Tao · Yingwen Wu · Cihang Xie · Xiaolin Huang

Revisiting Non-Parametric Matching Cost Volumes for Robust and Generalizable Stereo Matching

Kelvin Cheng · Tianfu Wu · Christopher Healey

Learning Contrastive Embedding in Low-Dimensional Space

Shuo Chen · Chen Gong · Jun Li · Jian Yang · Gang Niu · Masashi Sugiyama

Few-Shot Fast-Adaptive Anomaly Detection

Ze Wang · Yipin Zhou · Rui Wang · Tsung-Yu Lin · Ashish Shah · Ser Nam Lim

Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees

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

Exploration via Planning for Information about the Optimal Trajectory

Viraj Mehta · Ian Char · Joseph Abbate · Rory Conlin · Mark Boyer · Stefano Ermon · Jeff Schneider · Willie Neiswanger

Theoretical analysis of deep neural networks for temporally dependent observations

Mingliang Ma · Abolfazl Safikhani

Provably sample-efficient RL with side information about latent dynamics

Yao Liu · Dipendra Misra · Miro Dudik · Robert Schapire

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

Henry Kvinge · Tegan Emerson · Grayson Jorgenson · Scott Vasquez · Tim Doster · Jesse Lew

Truncated proposals for scalable and hassle-free simulation-based inference

Michael Deistler · Pedro Goncalves · Jakob H Macke

Calibrated Data-Dependent Constraints with Exact Satisfaction Guarantees

Songkai Xue · Yuekai Sun · Mikhail Yurochkin

Policy Optimization with Linear Temporal Logic Constraints

Cameron Voloshin · Hoang Le · Swarat Chaudhuri · Yisong Yue

Fast Instrument Learning with Faster Rates

Ziyu Wang · Yuhao Zhou · Jun Zhu

Outlier-Robust Sparse Estimation via Non-Convex Optimization

Yu Cheng · Ilias Diakonikolas · Rong Ge · Shivam Gupta · Daniel Kane · Mahdi Soltanolkotabi

Gradient Methods Provably Converge to Non-Robust Networks

Gal Vardi · Gilad Yehudai · Ohad Shamir

Operator Splitting Value Iteration

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

Bayesian Optimistic Optimization: Optimistic Exploration for Model-based Reinforcement Learning

Chenyang Wu · Tianci Li · Zongzhang Zhang · Yang Yu

Learning from Stochastically Revealed Preference

John Birge · Xiaocheng Li · Chunlin Sun

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

Akshay Mete · Rahul Singh · P. R. Kumar

An $\alpha$-No-Regret Algorithm For Graphical Bilinear Bandits

Geovani Rizk · Igor Colin · Albert Thomas · Rida Laraki · Yann Chevaleyre

Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions

Ilias Diakonikolas · Daniel Kane · Jasper Lee · Ankit Pensia

Distributed Inverse Constrained Reinforcement Learning for Multi-agent Systems

Shicheng Liu · Minghui Zhu

Uplifting Bandits

Yu-Guan Hsieh · Shiva Kasiviswanathan · Branislav Kveton

Poisson Flow Generative Models

Yilun Xu · Ziming Liu · Max Tegmark · Tommi Jaakkola

Multi-agent Dynamic Algorithm Configuration

Ke Xue · Jiacheng Xu · Lei Yuan · Miqing Li · Chao Qian · Zongzhang Zhang · Yang Yu

Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging

Edwige Cyffers · Mathieu Even · Aurélien Bellet · Laurent Massoulié

A Theory of PAC Learnability under Transformation Invariances

Han Shao · Omar Montasser · Avrim Blum

Lost in Latent Space: Examining failures of disentangled models at combinatorial generalisation

Milton Montero · Jeffrey Bowers · Rui Ponte Costa · Casimir Ludwig · Gaurav Malhotra

Biologically plausible solutions for spiking networks with efficient coding

Veronika Koren · Stefano Panzeri

Phase transitions in when feedback is useful

Lokesh Boominathan · Xaq Pitkow

Simple and Optimal Greedy Online Contention Resolution Schemes

Vasilis Livanos

Private Estimation with Public Data

Alex Bie · Gautam Kamath · Vikrant Singhal

Robustness to Label Noise Depends on the Shape of the Noise Distribution

Diane Oyen · Michal Kucer · Nicolas Hengartner · Har Simrat Singh

A general approximation lower bound in $L^p$ norm, with applications to feed-forward neural networks

El Mehdi Achour · Armand Foucault · Sébastien Gerchinovitz · François Malgouyres

Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification

Junpei Komiyama · Taira Tsuchiya · Junya Honda

Minimax Optimal Online Imitation Learning via Replay Estimation

Gokul Swamy · Nived Rajaraman · Matt Peng · Sanjiban Choudhury · J. Bagnell · Steven Wu · Jiantao Jiao · Kannan Ramchandran

Approximate Euclidean lengths and distances beyond Johnson-Lindenstrauss

Aleksandros Sobczyk · Mathieu Luisier

List-Decodable Sparse Mean Estimation

Shiwei Zeng · Jie Shen

Finite-Time Last-Iterate Convergence for Learning in Multi-Player Games

Yang Cai · Argyris Oikonomou · Weiqiang Zheng

SAGDA: Achieving $\mathcal{O}(\epsilon^{-2})$ Communication Complexity in Federated Min-Max Learning

Haibo Yang · Zhuqing Liu · Xin Zhang · Jia Liu

Depth is More Powerful than Width with Prediction Concatenation in Deep Forest

Shen-Huan Lyu · Yi-Xiao He · Zhi-Hua Zhou

Neural Abstractions

Alessandro Abate · Alec Edwards · Mirco Giacobbe

Random Rank: The One and Only Strategyproof and Proportionally Fair Randomized Facility Location Mechanism

Haris Aziz · Alexander Lam · Mashbat Suzuki · Toby Walsh

Smooth Fictitious Play in Stochastic Games with Perturbed Payoffs and Unknown Transitions

Lucas Baudin · Rida Laraki

The Query Complexity of Cake Cutting

Simina Branzei · Noam Nisan

Learning (Very) Simple Generative Models Is Hard

Sitan Chen · Jerry Li · Yuanzhi Li

Cryptographic Hardness of Learning Halfspaces with Massart Noise

Ilias Diakonikolas · Daniel Kane · Pasin Manurangsi · Lisheng Ren

Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Functions

Saeed Masiha · Saber Salehkaleybar · Niao He · Negar Kiyavash · Patrick Thiran

Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling

Dmitry Kovalev · Alexander Gasnikov · Peter Richtarik

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

Ziang Song · Song Mei · Yu Bai

SAPD+: An Accelerated Stochastic Method for Nonconvex-Concave Minimax Problems

Xuan Zhang · Necdet Serhat Aybat · Mert Gurbuzbalaban

On Optimal Learning Under Targeted Data Poisoning

Steve Hanneke · Amin Karbasi · Mohammad Mahmoody · Idan Mehalel · Shay Moran

Taming Fat-Tailed (“Heavier-Tailed” with Potentially Infinite Variance) Noise in Federated Learning

Haibo Yang · Peiwen Qiu · Jia Liu

Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs

Shinji Ito · Taira Tsuchiya · Junya Honda

Better Best of Both Worlds Bounds for Bandits with Switching Costs

Idan Amir · Guy Azov · Tomer Koren · Roi Livni

Coreset for Line-Sets Clustering

Sagi Lotan · Ernesto Evgeniy Sanches Shayda · Dan Feldman

On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood

Moses Charikar · Zhihao Jiang · Kirankumar Shiragur · Aaron Sidford

Society of Agents: Regret Bounds of Concurrent Thompson Sampling

Yan Chen · Perry Dong · Qinxun Bai · Maria Dimakopoulou · Wei Xu · Zhengyuan Zhou

Improved Convergence Rate of Stochastic Gradient Langevin Dynamics with Variance Reduction and its Application to Optimization

Yuri Kinoshita · Taiji Suzuki

Kernel Multimodal Continuous Attention

Alexander Moreno · Zhenke Wu · Supriya Nagesh · Walter Dempsey · James Rehg

Empirical Gateaux Derivatives for Causal Inference

Michael Jordan · Yixin Wang · Angela Zhou

Bayesian Persuasion for Algorithmic Recourse

Keegan Harris · Valerie Chen · Joon Kim · Ameet Talwalkar · Hoda Heidari · Steven Wu

Hardness of Noise-Free Learning for Two-Hidden-Layer Neural Networks

Sitan Chen · Aravind Gollakota · Adam Klivans · Raghu Meka

The Hessian Screening Rule

Johan Larsson · Jonas Wallin

Distributed Optimization for Overparameterized Problems: Achieving Optimal Dimension Independent Communication Complexity

Bingqing Song · Ioannis Tsaknakis · Chung-Yiu Yau · Hoi-To Wai · Mingyi Hong

Will Bilevel Optimizers Benefit from Loops

Kaiyi Ji · Mingrui Liu · Yingbin Liang · Lei Ying

Expected Improvement for Contextual Bandits

Hung Tran-The · Sunil Gupta · Santu Rana · Tuan Truong · Long Tran-Thanh · Svetha Venkatesh

Fast Neural Kernel Embeddings for General Activations

Insu Han · Amir Zandieh · Jaehoon Lee · Roman Novak · Lechao Xiao · Amin Karbasi

Maximum Common Subgraph Guided Graph Retrieval: Late and Early Interaction Networks

Indradyumna Roy · Soumen Chakrabarti · Abir De

Hierarchical Agglomerative Graph Clustering in Poly-Logarithmic Depth

Laxman Dhulipala · David Eisenstat · Jakub Lacki · Vahab Mirrokni · Jessica Shi

Understanding Deep Contrastive Learning via Coordinate-wise Optimization

Yuandong Tian

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

Dilip Arumugam · Benjamin Van Roy

Sparse Hypergraph Community Detection Thresholds in Stochastic Block Model

Erchuan Zhang · David Suter · Giang Truong · Syed Zulqarnain Gilani

Don't Pour Cereal into Coffee: Differentiable Temporal Logic for Temporal Action Segmentation

Ziwei Xu · Yogesh Rawat · Yongkang Wong · Mohan Kankanhalli · Mubarak Shah

Towards Versatile Embodied Navigation

Hanqing Wang · Wei Liang · Luc V Gool · Wenguan Wang

CASA: Category-agnostic Skeletal Animal Reconstruction

Yuefan Wu · Zeyuan Chen · Shaowei Liu · Zhongzheng Ren · Shenlong Wang

Counterfactual Neural Temporal Point Process for Estimating Causal Influence of Misinformation on Social Media

Yizhou Zhang · Defu Cao · Yan Liu

Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling

Junyuan Hong · Lingjuan Lyu · Jiayu Zhou · Michael Spranger

Brain Network Transformer

Xuan Kan · Wei Dai · Hejie Cui · Zilong Zhang · Ying Guo · Carl Yang

Policy Optimization with Advantage Regularization for Long-Term Fairness in Decision Systems

Eric Yu · Zhizhen Qin · Min Kyung Lee · Sicun Gao

SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks

Davide Buffelli · Pietro Lió · Fabio Vandin

The Phenomenon of Policy Churn

Tom Schaul · Andre Barreto · John Quan · Georg Ostrovski

Learning to Find Proofs and Theorems by Learning to Refine Search Strategies: The Case of Loop Invariant Synthesis

Jonathan Laurent · André Platzer

Censored Quantile Regression Neural Networks for Distribution-Free Survival Analysis

Tim Pearce · Jong-Hyeon Jeong · yichen jia · Jun Zhu

Certifying Robust Graph Classification under Orthogonal Gromov-Wasserstein Threats

Hongwei Jin · Zishun Yu · Xinhua Zhang

To update or not to update? Neurons at equilibrium in deep models

Andrea Bragagnolo · Enzo Tartaglione · Marco Grangetto

Improving Intrinsic Exploration with Language Abstractions

Jesse Mu · Victor Zhong · Roberta Raileanu · Minqi Jiang · Noah Goodman · Tim Rocktäschel · Edward Grefenstette

Masked Generative Adversarial Networks are Data-Efficient Generation Learners

Jiaxing Huang · Kaiwen Cui · Dayan Guan · Aoran Xiao · Fangneng Zhan · Shijian Lu · Shengcai Liao · Eric Xing

Dance of SNN and ANN: Solving binding problem by combining spike timing and reconstructive attention

Hao Zheng · Hui Lin · Rong Zhao · Luping Shi

Theseus: A Library for Differentiable Nonlinear Optimization

Luis Pineda · Taosha Fan · Maurizio Monge · Shobha Venkataraman · Paloma Sodhi · Ricky T. Q. Chen · Joseph Ortiz · Daniel DeTone · Austin Wang · Stuart Anderson · Jing Dong · Brandon Amos · Mustafa Mukadam

Distributed Influence-Augmented Local Simulators for Parallel MARL in Large Networked Systems

Miguel Suau · Jinke He · Mustafa Mert Çelikok · Matthijs Spaan · Frans Oliehoek

Synthetic Model Combination: An Instance-wise Approach to Unsupervised Ensemble Learning

Alex Chan · Mihaela van der Schaar

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

Eric Nguyen · Karan Goel · Albert Gu · Gordon Downs · Preey Shah · Tri Dao · Stephen Baccus · Christopher Ré

Decoupling Features in Hierarchical Propagation for Video Object Segmentation

Zongxin Yang · Yi Yang

Is Out-of-Distribution Detection Learnable?

Zhen Fang · Yixuan Li · Jie Lu · Jiahua Dong · Bo Han · Feng Liu

QUARK: Controllable Text Generation with Reinforced Unlearning

Ximing Lu · Sean Welleck · Jack Hessel · Liwei Jiang · Lianhui Qin · Peter West · Prithviraj Ammanabrolu · Yejin Choi

Dynamics of SGD with Stochastic Polyak Stepsizes: Truly Adaptive Variants and Convergence to Exact Solution

Antonio Orvieto · Simon Lacoste-Julien · Nicolas Loizou

Homomorphic Matrix Completion

Xiao-Yang Liu · Zechu (Steven) Li · Xiaodong Wang

Practical Adversarial Attacks on Spatiotemporal Traffic Forecasting Models

Fan LIU · Hao Liu · Wenzhao Jiang

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

Meenakshi Khosla · Keith Jamison · Amy Kuceyeski · Mert Sabuncu

GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images

Jun Gao · Tianchang Shen · Zian Wang · Wenzheng Chen · Kangxue Yin · Daiqing Li · Or Litany · Zan Gojcic · Sanja Fidler

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

Julien Colin · Thomas FEL · Remi Cadene · Thomas Serre

CLIPDraw: Exploring Text-to-Drawing Synthesis through Language-Image Encoders

Kevin Frans · Lisa Soros · Olaf Witkowski

VisFIS: Visual Feature Importance Supervision with Right-for-the-Right-Reason Objectives

Zhuofan Ying · Peter Hase · Mohit Bansal

Accelerated Training of Physics-Informed Neural Networks (PINNs) using Meshless Discretizations

Ramansh Sharma · Varun Shankar

On the Importance of Gradient Norm in PAC-Bayesian Bounds

Itai Gat · Yossi Adi · Alex Schwing · Tamir Hazan

Temporally Disentangled Representation Learning

Weiran Yao · Guangyi Chen · Kun Zhang

Natural gradient enables fast sampling in spiking neural networks

Paul Masset · Jacob Zavatone-Veth · J. Patrick Connor · Venkatesh Murthy · Cengiz Pehlevan

Triangulation candidates for Bayesian optimization

Robert Gramacy · Annie Sauer · Nathan Wycoff

Near-Isometric Properties of Kronecker-Structured Random Tensor Embeddings

Qijia Jiang

A permutation-free kernel two-sample test

Shubhanshu Shekhar · Ilmun Kim · Aaditya Ramdas

Exponential Family Model-Based Reinforcement Learning via Score Matching

Gene Li · Junbo Li · Anmol Kabra · Nati Srebro · Zhaoran Wang · Zhuoran Yang

Learning with little mixing

Ingvar Ziemann · Stephen Tu

Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds

Aritra Mitra · Arman Adibi · George J. Pappas · Hamed Hassani

Communication Efficient Federated Learning for Generalized Linear Bandits

Chuanhao Li · Hongning Wang

On Scrambling Phenomena for Randomly Initialized Recurrent Networks

Vaggos Chatziafratis · Ioannis Panageas · Clayton Sanford · Stelios Stavroulakis

Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks

Anders Aamand · Justin Chen · Piotr Indyk · Shyam Narayanan · Ronitt Rubinfeld · Nicholas Schiefer · Sandeep Silwal · Tal Wagner

Last-Iterate Convergence of Optimistic Gradient Method for Monotone Variational Inequalities

Eduard Gorbunov · Adrien Taylor · Gauthier Gidel

3DB: A Framework for Debugging Computer Vision Models

Guillaume Leclerc · Hadi Salman · Andrew Ilyas · Sai Vemprala · Logan Engstrom · Vibhav Vineet · Kai Xiao · Pengchuan Zhang · Shibani Santurkar · Greg Yang · Ashish Kapoor · Aleksander Madry

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

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

Measuring Data Reconstruction Defenses in Collaborative Inference Systems

Mengda Yang · Ziang Li · Juan Wang · Hongxin Hu · Ao Ren · Xiaoyang Xu · Wenzhe Yi

Function Classes for Identifiable Nonlinear Independent Component Analysis

Simon Buchholz · Michel Besserve · Bernhard Schölkopf

Towards Disentangling Information Paths with Coded ResNeXt

Apostolos Avranas · Marios Kountouris

Why do We Need Large Batchsizes in Contrastive Learning? A Gradient-Bias Perspective

Changyou Chen · Jianyi Zhang · Yi Xu · Liqun Chen · Jiali Duan · Yiran Chen · Son Tran · Belinda Zeng · Trishul Chilimbi

On Robust Multiclass Learnability

Jingyuan Xu · Weiwei Liu

Generalised Mutual Information for Discriminative Clustering

Louis Ohl · Pierre-Alexandre Mattei · Charles Bouveyron · Warith HARCHAOUI · Mickaël Leclercq · Arnaud Droit · Frederic Precioso

A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning

Bo Liu · Xidong Feng · Jie Ren · Luo Mai · Rui Zhu · Haifeng Zhang · Jun Wang · Yaodong Yang

Anytime-Valid Inference For Multinomial Count Data

Michael Lindon · Alan Malek

OpenOOD: Benchmarking Generalized Out-of-Distribution Detection

Jingkang Yang · Pengyun Wang · Dejian Zou · Zitang Zhou · Kunyuan Ding · WENXUAN PENG · Haoqi Wang · Guangyao Chen · Bo Li · Yiyou Sun · Xuefeng Du · Kaiyang Zhou · Wayne Zhang · Dan Hendrycks · Yixuan Li · Ziwei Liu

FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning

Xiao-Yang Liu · Ziyi Xia · Jingyang Rui · Jiechao Gao · Hongyang Yang · Ming Zhu · Christina Wang · Zhaoran Wang · Jian Guo

NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse Tasks

Renbo Tu · Nicholas Roberts · Misha Khodak · Junhong Shen · Frederic Sala · Ameet Talwalkar

ETAB: A Benchmark Suite for Visual Representation Learning in Echocardiography

Ahmed M. Alaa · Anthony Philippakis · David Sontag

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

Sérgio Jesus · José Pombal · Duarte Alves · André Cruz · Pedro Saleiro · Rita Ribeiro · João Gama · Pedro Bizarro

How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning?

Chengxu Zhuang · Ziyu Xiang · Yoon Bai · Xiaoxuan Jia · Nicholas Turk-Browne · Kenneth Norman · James J DiCarlo · Dan Yamins

ActionSense: A Multimodal Dataset and Recording Framework for Human Activities Using Wearable Sensors in a Kitchen Environment

Joseph DelPreto · Chao Liu · Yiyue Luo · Michael Foshey · Yunzhu Li · Antonio Torralba · Wojciech Matusik · Daniela Rus

Breaking Bad: A Dataset for Geometric Fracture and Reassembly

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

FlyView: a bio-informed optical flow truth dataset for visual navigation using panoramic stereo vision

Alix Leroy · Graham Taylor

Chartalist: Labeled Graph Datasets for UTXO and Account-based Blockchains

Kiarash Shamsi · Friedhelm Victor · Murat Kantarcioglu · Yulia Gel · Cuneyt G Akcora

SMPL: Simulated Industrial Manufacturing and Process Control Learning Environments

Mohan Zhang · Xiaozhou Wang · Benjamin Decardi-Nelson · Bo Song · An Zhang · Jinfeng Liu · Sile Tao · Jiayi Cheng · Xiaohong Liu · Dengdeng Yu · Matthew Poon · Animesh Garg

WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language Models

Yonatan Bitton · Nitzan Bitton Guetta · Ron Yosef · Yuval Elovici · Mohit Bansal · Gabriel Stanovsky · Roy Schwartz

MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction

Jorge Quesada · Lakshmi Sathidevi · Ran Liu · Nauman Ahad · Joy Jackson · Mehdi Azabou · Jingyun Xiao · Christopher Liding · Matthew Jin · Carolina Urzay · William Gray-Roncal · Erik Johnson · Eva Dyer

xView3-SAR: Detecting Dark Fishing Activity Using Synthetic Aperture Radar Imagery

Fernando Paolo · Tsu-ting Tim Lin · Ritwik Gupta · Bryce Goodman · Nirav Patel · Daniel Kuster · David Kroodsma · Jared Dunnmon

CEDe: A collection of expert-curated datasets with atom-level entity annotations for Optical Chemical Structure Recognition

Rodrigo Hormazabal · Changyoung Park · Soonyoung Lee · Sehui Han · Yeonsik Jo · Jaewan Lee · Ahra Jo · Seung Hwan Kim · Jaegul Choo · Moontae Lee · Honglak Lee

FETA: Towards Specializing Foundational Models for Expert Task Applications

Amit Alfassy · Assaf Arbelle · Oshri Halimi · Sivan Harary · Roei Herzig · Eli Schwartz · Rameswar Panda · Michele Dolfi · Christoph Auer · Peter Staar · Kate Saenko · Rogerio Feris · Leonid Karlinsky

CAESAR: An Embodied Simulator for Generating Multimodal Referring Expression Datasets

Md Mofijul Islam · Reza Mirzaiee · Alexi Gladstone · Haley Green · Tariq Iqbal

Evaluating Out-of-Distribution Performance on Document Image Classifiers

Stefan Larson · Yi Yang Gordon Lim · Yutong Ai · David Kuang · Kevin Leach

Learning Long-Term Crop Management Strategies with CyclesGym

Matteo Turchetta · Luca Corinzia · Scott Sussex · Amanda Burton · Juan Herrera · Ioannis Athanasiadis · Joachim M Buhmann · Andreas Krause

pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning

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

Myriad: a real-world testbed to bridge trajectory optimization and deep learning

Nikolaus Howe · Simon Dufort-Labbé · Nitarshan Rajkumar · Pierre-Luc Bacon

Deep Limits and a Cut-Off Phenomenon for Neural Networks

Benny Avelin · Anders Karlsson

Non-asymptotic and Accurate Learning of Nonlinear Dynamical Systems

Yahya Sattar · Samet Oymak

Robust and scalable manifold learning via landmark diffusion for long-term medical signal processing

Chao Shen · Yu-Ting Lin · Hau-Tieng Wu

The Importance of Being Correlated: Implications of Dependence in Joint Spectral Inference across Multiple Networks

Konstantinos Pantazis · Avanti Athreya · Jesus Arroyo · William N Frost · Evan S Hill · Vince Lyzinski

Foolish Crowds Support Benign Overfitting

Niladri S. Chatterji · Philip Long

[Re] Exacerbating Algorithmic Bias through Fairness Attacks

Angelos Nalmpantis · Apostolos Panagiotopoulos · John Gkountouras · Konstantinos Papakostas

[Re] Replication Study of "Fairness and Bias in Online Selection"

Diego van der Mast · Soufiane Ben Haddou · Jacky Chu · Jaap Stefels

[Re] Reproduction Study of Variational Fair Clustering

Floor Eijkjelboom · Mark Fokkema · Anna Lau · Luuk Verheijen

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Invited Talk

Conformal Prediction in 2022

Emmanuel Candes

2:30 PM - 3:30 PM

Conformal inference methods are becoming all the rage in academia and industry alike. In a nutshell, these methods deliver exact prediction intervals for future observations without making any distributional assumption whatsoever other than having iid, and more generally, exchangeable data. This talk will review the basic principles underlying conformal inference and survey some major contributions that have occurred in the last 2-3 years or. We will discuss enhanced conformity scores applicable to quantitative as well as categorical labels. We will also survey novel methods which deal with situations, where the distribution of observations can shift drastically — think of finance or economics where market behavior can change over time in response to new legislation or major world events, or public health where changes occur because of geography and/or policies. All along, we shall illustrate the methods with examples including the prediction of election results or COVID19-case trajectories.

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Poster

Poster Session 2

4:00 PM - 6:00 PM

417 Events in this session

A Nonconvex Framework for Structured Dynamic Covariance Recovery

Katherine Tsai · Mladen Kolar · Sanmi Koyejo

Alignment-guided Temporal Attention for Video Action Recognition

Yizhou Zhao · Zhenyang Li · Xun Guo · Yan Lu

TCT: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels

Yaodong Yu · Alexander Wei · Sai Praneeth Karimireddy · Yi Ma · Michael Jordan

On Feature Learning in the Presence of Spurious Correlations

Pavel Izmailov · Polina Kirichenko · Nate Gruver · Andrew Wilson

Spatial Mixture-of-Experts

Nikoli Dryden · Torsten Hoefler

Exploring Length Generalization in Large Language Models

Cem Anil · Yuhuai Wu · Anders Andreassen · Aitor Lewkowycz · Vedant Misra · Vinay Ramasesh · Ambrose Slone · Guy Gur-Ari · Ethan Dyer · Behnam Neyshabur

Neural Topological Ordering for Computation Graphs

Mukul Gagrani · Corrado Rainone · Yang Yang · Harris Teague · Wonseok Jeon · Roberto Bondesan · Herke van Hoof · Christopher Lott · Weiliang Zeng · Piero Zappi

Unsupervised Multi-View Object Segmentation Using Radiance Field Propagation

Xinhang Liu · Jiaben Chen · Huai Yu · Yu-Wing Tai · Chi-Keung Tang

Offline Multi-Agent Reinforcement Learning with Knowledge Distillation

Wei-Cheng Tseng · Tsun-Hsuan Johnson Wang · Yen-Chen Lin · Phillip Isola

Enhanced Meta Reinforcement Learning via Demonstrations in Sparse Reward Environments

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

Maximum Class Separation as Inductive Bias in One Matrix

Tejaswi Kasarla · Gertjan Burghouts · Max van Spengler · Elise van der Pol · Rita Cucchiara · Pascal Mettes

Training Uncertainty-Aware Classifiers with Conformalized Deep Learning

Bat-Sheva Einbinder · Yaniv Romano · Matteo Sesia · Yanfei Zhou

Efficiently Factorizing Boolean Matrices using Proximal Gradient Descent

Sebastian Dalleiger · Jilles Vreeken

FlowHMM: Flow-based continuous hidden Markov models

Pawel Lorek · Rafal Nowak · Tomasz Trzcinski · Maciej Zieba

Merging Models with Fisher-Weighted Averaging

Michael S Matena · Colin Raffel

Holomorphic Equilibrium Propagation Computes Exact Gradients Through Finite Size Oscillations

Axel Laborieux · Friedemann Zenke

Neural Payoff Machines: Predicting Fair and Stable Payoff Allocations Among Team Members

Daphne Cornelisse · Thomas Rood · Yoram Bachrach · Mateusz Malinowski · Tal Kachman

Additive MIL: Intrinsically Interpretable Multiple Instance Learning for Pathology

Syed Ashar Javed · Dinkar Juyal · Harshith Padigela · Amaro Taylor-Weiner · Limin Yu · Aaditya Prakash

Making Look-Ahead Active Learning Strategies Feasible with Neural Tangent Kernels

Mohamad Amin Mohamadi · Wonho Bae · Danica J. Sutherland

Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse

Lorenzo Noci · Sotiris Anagnostidis · Luca Biggio · Antonio Orvieto · Sidak Pal Singh · Aurelien Lucchi

Ordered Subgraph Aggregation Networks

Chendi Qian · Gaurav Rattan · Floris Geerts · Mathias Niepert · Christopher Morris

Infinite Recommendation Networks: A Data-Centric Approach

Noveen Sachdeva · Mehak Dhaliwal · Carole-Jean Wu · Julian Mcauley

Diversity vs. Recognizability: Human-like generalization in one-shot generative models

Victor Boutin · Lakshya Singhal · Xavier Thomas · Thomas Serre

Geo-SIC: Learning Deformable Geometric Shapes in Deep Image Classifiers

Jian Wang · Miaomiao Zhang

Improving Transformer with an Admixture of Attention Heads

Tan Nguyen · Tam Nguyen · Hai Do · Khai Nguyen · Vishwanath Saragadam · Minh Pham · Khuong Duy Nguyen · Nhat Ho · Stanley Osher

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

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

Information-Theoretic GAN Compression with Variational Energy-based Model

Minsoo Kang · Hyewon Yoo · Eunhee Kang · Sehwan Ki · Hyong Euk Lee · Bohyung Han

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

Che Wang · Xufang Luo · Keith Ross · Dongsheng Li

CLEAR: Generative Counterfactual Explanations on Graphs

Jing Ma · Ruocheng Guo · Saumitra Mishra · Aidong Zhang · Jundong Li

Out-of-Distribution Detection with An Adaptive Likelihood Ratio on Informative Hierarchical VAE

Yewen Li · Chaojie Wang · Xiaobo Xia · Tongliang Liu · xin miao · Bo An

Adversarial Style Augmentation for Domain Generalized Urban-Scene Segmentation

Zhun Zhong · Yuyang Zhao · Gim Hee Lee · Nicu Sebe

A Coupled Design of Exploiting Record Similarity for Practical Vertical Federated Learning

Zhaomin Wu · Qinbin Li · Bingsheng He

ClimbQ: Class Imbalanced Quantization Enabling Robustness on Efficient Inferences

Ting-An Chen · De-Nian Yang · Ming-syan Chen

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

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

SIREN: Shaping Representations for Detecting Out-of-Distribution Objects

Xuefeng Du · Gabriel Gozum · Yifei Ming · Yixuan Li

Efficient and Effective Multi-task Grouping via Meta Learning on Task Combinations

Xiaozhuang Song · Shun Zheng · Wei Cao · James Yu · Jiang Bian

DENSE: Data-Free One-Shot Federated Learning

Jie Zhang · Chen Chen · Bo Li · Lingjuan Lyu · Shuang Wu · Shouhong Ding · Chunhua Shen · Chao Wu

SparCL: Sparse Continual Learning on the Edge

Zifeng Wang · Zheng Zhan · Yifan Gong · Geng Yuan · Wei Niu · Tong Jian · Bin Ren · Stratis Ioannidis · Yanzhi Wang · Jennifer Dy

Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again

AJAY JAISWAL · Peihao Wang · Tianlong Chen · Justin Rousseau · Ying Ding · Zhangyang Wang

Multi-modal Grouping Network for Weakly-Supervised Audio-Visual Video Parsing

Shentong Mo · Yapeng Tian

Searching for Better Spatio-temporal Alignment in Few-Shot Action Recognition

Yichao Cao · Xiu Su · Qingfei Tang · Shan You · Xiaobo Lu · Chang Xu

Learning Generalizable Part-based Feature Representation for 3D Point Clouds

Xin Wei · Xiang Gu · Jian Sun

Coordinates Are NOT Lonely - Codebook Prior Helps Implicit Neural 3D representations

Fukun Yin · Wen Liu · Zilong Huang · Pei Cheng · Tao Chen · Gang Yu

Set-based Meta-Interpolation for Few-Task Meta-Learning

Seanie Lee · Bruno Andreis · Kenji Kawaguchi · Juho Lee · Sung Ju Hwang

Zero-Shot Video Question Answering via Frozen Bidirectional Language Models

Antoine Yang · Antoine Miech · Josef Sivic · Ivan Laptev · Cordelia Schmid

Masked Autoencoders As Spatiotemporal Learners

Christoph Feichtenhofer · haoqi fan · Yanghao Li · Kaiming He

Uncovering the Structural Fairness in Graph Contrastive Learning

Ruijia Wang · Xiao Wang · Chuan Shi · Le Song

AutoMS: Automatic Model Selection for Novelty Detection with Error Rate Control

Yifan Zhang · Haiyan Jiang · Haojie Ren · Changliang Zou · Dejing Dou

Learning Best Combination for Efficient N:M Sparsity

Yuxin Zhang · Mingbao Lin · ZhiHang Lin · Yiting Luo · Ke Li · Fei Chao · Yongjian Wu · Rongrong Ji

C-Mixup: Improving Generalization in Regression

Huaxiu Yao · Yiping Wang · Linjun Zhang · James Zou · Chelsea Finn

GAPX: Generalized Autoregressive Paraphrase-Identification X

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

Exploring the Limits of Domain-Adaptive Training for Detoxifying Large-Scale Language Models

Boxin Wang · Wei Ping · Chaowei Xiao · Peng Xu · Mostofa Patwary · Mohammad Shoeybi · Bo Li · Anima Anandkumar · Bryan Catanzaro

GAMA: Generative Adversarial Multi-Object Scene Attacks

Abhishek Aich · Calvin-Khang Ta · Akash Gupta · Chengyu Song · Srikanth Krishnamurthy · Salman Asif · Amit Roy-Chowdhury

Composite Feature Selection Using Deep Ensembles

Fergus Imrie · Alexander Norcliffe · Pietro Lió · Mihaela van der Schaar

Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods

Randall Balestriero · Yann LeCun

Discovered Policy Optimisation

Chris Lu · Jakub Kuba · Alistair Letcher · Luke Metz · Christian Schroeder de Witt · Jakob Foerster

Learning Structure from the Ground up---Hierarchical Representation Learning by Chunking

Shuchen Wu · Noemi Elteto · Ishita Dasgupta · Eric Schulz

Amortized Inference for Heterogeneous Reconstruction in Cryo-EM

Axel Levy · Gordon Wetzstein · Julien N.P Martel · Frederic Poitevin · Ellen Zhong

Neural Approximation of Graph Topological Features

Zuoyu Yan · Tengfei Ma · Liangcai Gao · Zhi Tang · Yusu Wang · Chao Chen

Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment

Chenxiao Yang · Qitian Wu · Qingsong Wen · Zhiqiang Zhou · Liang Sun · Junchi Yan

Improving Variational Autoencoders with Density Gap-based Regularization

Jianfei Zhang · Jun Bai · Chenghua Lin · Yanmeng Wang · Wenge Rong

End-to-end Stochastic Optimization with Energy-based Model

Lingkai Kong · Jiaming Cui · Yuchen Zhuang · Rui Feng · B. Aditya Prakash · Chao Zhang

Physics-Embedded Neural Networks: Graph Neural PDE Solvers with Mixed Boundary Conditions

Masanobu Horie · NAOTO MITSUME

Advancing Model Pruning via Bi-level Optimization

Yihua Zhang · Yuguang Yao · Parikshit Ram · Pu Zhao · Tianlong Chen · Mingyi Hong · Yanzhi Wang · Sijia Liu

Earthformer: Exploring Space-Time Transformers for Earth System Forecasting

Zhihan Gao · Xingjian Shi · Hao Wang · Yi Zhu · Yuyang (Bernie) Wang · Mu Li · Dit-Yan Yeung

Is Integer Arithmetic Enough for Deep Learning Training?

Alireza Ghaffari · Marzieh S. Tahaei · Mohammadreza Tayaranian · Masoud Asgharian · Vahid Partovi Nia

Dense Interspecies Face Embedding

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

Learning State-Aware Visual Representations from Audible Interactions

Himangi Mittal · Pedro Morgado · Unnat Jain · Abhinav Gupta

VITA: Video Instance Segmentation via Object Token Association

Miran Heo · Sukjun Hwang · Seoung Wug Oh · Joon-Young Lee · Seon Joo Kim

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

Leyan Deng · Defu Lian · Chenwang Wu · Enhong Chen

Pyramid Attention For Source Code Summarization

Lei Chai · Ming LI

An Empirical Study on Disentanglement of Negative-free Contrastive Learning

Jinkun Cao · Ruiqian Nai · Qing Yang · Jialei Huang · Yang Gao

Cache-Augmented Inbatch Importance Resampling for Training Recommender Retriever

Jin Chen · Defu Lian · Yucheng Li · Baoyun Wang · Kai Zheng · Enhong Chen

Draft-and-Revise: Effective Image Generation with Contextual RQ-Transformer

Doyup Lee · Chiheon Kim · Saehoon Kim · Minsu Cho · WOOK SHIN HAN

Get More at Once: Alternating Sparse Training with Gradient Correction

Li Yang · Jian Meng · Jae-sun Seo · Deliang Fan

Uncertainty Estimation for Multi-view Data: The Power of Seeing the Whole Picture

Myong Chol Jung · He Zhao · Joanna Dipnall · Belinda Gabbe · Lan Du

Synergy-of-Experts: Collaborate to Improve Adversarial Robustness

Sen Cui · Jingfeng ZHANG · Jian Liang · Bo Han · Masashi Sugiyama · Changshui Zhang

Accelerating Certified Robustness Training via Knowledge Transfer

Pratik Vaishnavi · Kevin Eykholt · Amir Rahmati

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

Xiang Zhang · Ziyuan Zhao · Theodoros Tsiligkaridis · Marinka Zitnik

Self-supervised Amodal Video Object Segmentation

Jian Yao · Yuxin Hong · Chiyu Wang · Tianjun Xiao · Tong He · Francesco Locatello · David P Wipf · Yanwei Fu · Zheng Zhang

Rethinking Image Restoration for Object Detection

Shangquan Sun · Wenqi Ren · Tao Wang · Xiaochun Cao

Unsupervised Learning of Shape Programs with Repeatable Implicit Parts

Boyang Deng · Sumith Kulal · Zhengyang Dong · Congyue Deng · Yonglong Tian · Jiajun Wu

ELASTIC: Numerical Reasoning with Adaptive Symbolic Compiler

Jiaxin Zhang · Yashar Moshfeghi

Learning dynamics of deep linear networks with multiple pathways

Jianghong Shi · Eric Shea-Brown · Michael Buice

FP8 Quantization: The Power of the Exponent

Andrey Kuzmin · Mart van Baalen · Yuwei Ren · Markus Nagel · Jorn Peters · Tijmen Blankevoort

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

Brian Hsu · Rahul Mazumder · Preetam Nandy · Kinjal Basu

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

Vladimir Kostic · Pietro Novelli · Andreas Maurer · Carlo Ciliberto · Lorenzo Rosasco · Massimiliano Pontil

Pseudo-Riemannian Graph Convolutional Networks

Bo Xiong · Shichao Zhu · Nico Potyka · Shirui Pan · Chuan Zhou · Steffen Staab

PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization

Sanae Lotfi · Marc Finzi · Sanyam Kapoor · Andres Potapczynski · Micah Goldblum · Andrew Wilson

Learning Mixed Multinomial Logits with Provable Guarantees

Yiqun Hu · David Simchi-Levi · Zhenzhen Yan

Truly Deterministic Policy Optimization

Ehsan Saleh · Saba Ghaffari · Tim Bretl · Matthew West

A Consistent and Differentiable Lp Canonical Calibration Error Estimator

Teodora Popordanoska · Raphael Sayer · Matthew Blaschko

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

Lior Danon · Dan Garber

Reinforcement Learning with Logarithmic Regret and Policy Switches

Grigoris Velegkas · Zhuoran Yang · Amin Karbasi

Finite Sample Analysis Of Dynamic Regression Parameter Learning

Mark Kozdoba · Edward Moroshko · Shie Mannor · Yacov Crammer

Evaluating Robustness to Dataset Shift via Parametric Robustness Sets

Nikolaj Thams · Michael Oberst · David Sontag

Network change point localisation under local differential privacy

Mengchu Li · Tom Berrett · Yi Yu

When Privacy Meets Partial Information: A Refined Analysis of Differentially Private Bandits

Achraf Azize · Debabrota Basu

Diversified Recommendations for Agents with Adaptive Preferences

William Brown · Arpit Agarwal

Confident Approximate Policy Iteration for Efficient Local Planning in $q^\pi$-realizable MDPs

Gellért Weisz · András György · Tadashi Kozuno · Csaba Szepesvari

Parameter-free Regret in High Probability with Heavy Tails

Jiujia Zhang · Ashok Cutkosky

Shape And Structure Preserving Differential Privacy

Carlos Soto · Karthik Bharath · Matthew Reimherr · Aleksandra Slavković

Multi-layer State Evolution Under Random Convolutional Design

Max Daniels · Cedric Gerbelot · Florent Krzakala · Lenka Zdeborová

Graph Neural Networks with Adaptive Readouts

David Buterez · Jon Paul Janet · Steven J Kiddle · Dino Oglic · Pietro Liò

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

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

Causally motivated multi-shortcut identification and removal

Jiayun Zheng · Maggie Makar

Learning Predictions for Algorithms with Predictions

Misha Khodak · Maria-Florina Balcan · Ameet Talwalkar · Sergei Vassilvitskii

Near-Optimal Collaborative Learning in Bandits

Clémence Réda · Sattar Vakili · Emilie Kaufmann

Incentivizing Combinatorial Bandit Exploration

Xinyan Hu · Dung Ngo · Aleksandrs Slivkins · Steven Wu

BR-SNIS: Bias Reduced Self-Normalized Importance Sampling

Gabriel Cardoso · Sergey Samsonov · Achille Thin · Eric Moulines · Jimmy Olsson

Differentially Private Learning with Margin Guarantees

Raef Bassily · Mehryar Mohri · Ananda Theertha Suresh

Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes

Alkis Kalavasis · Grigoris Velegkas · Amin Karbasi

Planning to the Information Horizon of BAMDPs via Epistemic State Abstraction

Dilip Arumugam · Satinder Singh

Pay attention to your loss : understanding misconceptions about Lipschitz neural networks

Louis Béthune · Thibaut Boissin · Mathieu Serrurier · Franck Mamalet · Corentin Friedrich · Alberto Gonzalez Sanz

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

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

Data-Driven Offline Decision-Making via Invariant Representation Learning

Han Qi · Yi Su · Aviral Kumar · Sergey Levine

Learning Manifold Dimensions with Conditional Variational Autoencoders

Yijia Zheng · Tong He · Yixuan Qiu · David P Wipf

Asymptotics of $\ell_2$ Regularized Network Embeddings

Andrew Davison

TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets

Chengrun Yang · Gabriel Bender · Hanxiao Liu · Pieter-Jan Kindermans · Madeleine Udell · Yifeng Lu · Quoc V Le · Da Huang

Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post Hoc Explanations

Tessa Han · Suraj Srinivas · Himabindu Lakkaraju

CS-Shapley: Class-wise Shapley Values for Data Valuation in Classification

Stephanie Schoch · Haifeng Xu · Yangfeng Ji

Teacher Forcing Recovers Reward Functions for Text Generation

Yongchang Hao · Yuxin Liu · Lili Mou

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

Paul Novello · Thomas FEL · David Vigouroux

MGNNI: Multiscale Graph Neural Networks with Implicit Layers

Juncheng Liu · Bryan Hooi · Kenji Kawaguchi · Xiaokui Xiao

Gaussian Copula Embeddings

Chien Lu · Jaakko Peltonen

On Learning Fairness and Accuracy on Multiple Subgroups

Changjian Shui · Gezheng Xu · Qi CHEN · Jiaqi Li · Charles Ling · Tal Arbel · Boyu Wang · Christian Gagné

Mind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning

Victor Weixin Liang · Yuhui Zhang · Yongchan Kwon · Serena Yeung · James Zou

Sequencer: Deep LSTM for Image Classification

Yuki Tatsunami · Masato Taki

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

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

Sound and Complete Verification of Polynomial Networks

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

DReS-FL: Dropout-Resilient Secure Federated Learning for Non-IID Clients via Secret Data Sharing

Jiawei Shao · Yuchang Sun · Songze Li · Jun Zhang

Generalized Laplacian Eigenmaps

Hao Zhu · Piotr Koniusz

Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances

Sloan Nietert · Ziv Goldfeld · Ritwik Sadhu · Kengo Kato

Anchor-Changing Regularized Natural Policy Gradient for Multi-Objective Reinforcement Learning

Ruida Zhou · Tao Liu · Dileep Kalathil · P. R. Kumar · Chao Tian

RKHS-SHAP: Shapley Values for Kernel Methods

Siu Lun Chau · Robert Hu · Javier González · Dino Sejdinovic

Temporally-Consistent Survival Analysis

Lucas Maystre · Daniel Russo

ULNeF: Untangled Layered Neural Fields for Mix-and-Match Virtual Try-On

Igor Santesteban · Miguel Otaduy · Nils Thuerey · Dan Casas

Diffusion-based Molecule Generation with Informative Prior Bridges

Lemeng Wu · Chengyue Gong · Xingchao Liu · Mao Ye · Qiang Liu

Learning with convolution and pooling operations in kernel methods

Theodor Misiakiewicz · Song Mei

Optimizing Relevance Maps of Vision Transformers Improves Robustness

Hila Chefer · Idan Schwartz · Lior Wolf

Unsupervised Causal Generative Understanding of Images

Titas Anciukevicius · Patrick Fox-Roberts · Edward Rosten · Paul Henderson

SelecMix: Debiased Learning by Contradicting-pair Sampling

Inwoo Hwang · Sangjun Lee · Yunhyeok Kwak · Seong Joon Oh · Damien Teney · Jin-Hwa Kim · Byoung-Tak Zhang

Controllable Text Generation with Neurally-Decomposed Oracle

Tao Meng · Sidi Lu · Nanyun Peng · Kai-Wei Chang

Explain My Surprise: Learning Efficient Long-Term Memory by predicting uncertain outcomes

Artyom Sorokin · Nazar Buzun · Leonid Pugachev · Mikhail Burtsev

Rethinking Resolution in the Context of Efficient Video Recognition

Chuofan Ma · Qiushan Guo · Yi Jiang · Ping Luo · Zehuan Yuan · Xiaojuan Qi

Unsupervised Visual Representation Learning via Mutual Information Regularized Assignment

Dong Hoon Lee · Sungik Choi · Hyunwoo Kim · Sae-Young Chung

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

Haokun Liu · Derek Tam · Mohammed Muqeeth · Jay Mohta · Tenghao Huang · Mohit Bansal · Colin Raffel

Infinite-Fidelity Coregionalization for Physical Simulation

Shibo Li · Zheng Wang · Robert Kirby · Shandian Zhe

Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost

Sungjun Cho · Seonwoo Min · Jinwoo Kim · Moontae Lee · Honglak Lee · Seunghoon Hong

Private Set Generation with Discriminative Information

Dingfan Chen · Raouf Kerkouche · Mario Fritz

Private Synthetic Data for Multitask Learning and Marginal Queries

Giuseppe Vietri · Cedric Archambeau · Sergul Aydore · William Brown · Michael Kearns · Aaron Roth · Ankit Siva · Shuai Tang · Steven Wu

Deep Equilibrium Approaches to Diffusion Models

Ashwini Pokle · Zhengyang Geng · J. Zico Kolter

A Reparametrization-Invariant Sharpness Measure Based on Information Geometry

Cheongjae Jang · Sungyoon Lee · Frank Park · Yung-Kyun Noh

A Statistical Online Inference Approach in Averaged Stochastic Approximation

Chuhan Xie · Zhihua Zhang

Understanding Square Loss in Training Overparametrized Neural Network Classifiers

Tianyang Hu · Jun WANG · Wenjia Wang · Zhenguo Li

A Deep Reinforcement Learning Framework for Column Generation

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

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

Albert Wilcox · Ashwin Balakrishna · Jules Dedieu · Wyame Benslimane · Daniel Brown · Ken Goldberg

Models Out of Line: A Fourier Lens on Distribution Shift Robustness

Sara Fridovich-Keil · Brian Bartoldson · James Diffenderfer · Bhavya Kailkhura · Timo Bremer

Pre-Trained Language Models for Interactive Decision-Making

Shuang Li · Xavier Puig · Chris Paxton · Yilun Du · Clinton Wang · Linxi Fan · Tao Chen · De-An Huang · Ekin Akyürek · Anima Anandkumar · Jacob Andreas · Igor Mordatch · Antonio Torralba · Yuke Zhu

The Neural Testbed: Evaluating Joint Predictions

Ian Osband · Zheng Wen · Seyed Mohammad Asghari · Vikranth Dwaracherla · Xiuyuan Lu · MORTEZA IBRAHIMI · Dieterich Lawson · Botao Hao · Brendan O'Donoghue · Benjamin Van Roy

Is a Modular Architecture Enough?

Sarthak Mittal · Yoshua Bengio · Guillaume Lajoie

A theory of weight distribution-constrained learning

Weishun Zhong · Ben Sorscher · Daniel Lee · Haim Sompolinsky

Fast Bayesian Estimation of Point Process Intensity as Function of Covariates

Hideaki Kim · Taichi Asami · Hiroyuki Toda

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

Kyoungseok Jang · Chicheng Zhang · Kwang-Sung Jun

Parallel Tempering With a Variational Reference

Nikola Surjanovic · Saifuddin Syed · Alexandre Bouchard-Côté · Trevor Campbell

Embrace the Gap: VAEs Perform Independent Mechanism Analysis

Patrik Reizinger · Luigi Gresele · Jack Brady · Julius von Kügelgen · Dominik Zietlow · Bernhard Schölkopf · Georg Martius · Wieland Brendel · Michel Besserve

Learning Deep Input-Output Stable Dynamics

Ryosuke Kojima · Yuji Okamoto

Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation

Arnaud Delaunoy · Joeri Hermans · François Rozet · Antoine Wehenkel · Gilles Louppe

Hyperbolic Embedding Inference for Structured Multi-Label Prediction

Bo Xiong · Michael Cochez · Mojtaba Nayyeri · Steffen Staab

Surprising Instabilities in Training Deep Networks and a Theoretical Analysis

Yuxin Sun · DONG LAO · Ganesh Sundaramoorthi · Anthony Yezzi

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

Michael Chang · Tom Griffiths · Sergey Levine

Boosting the Performance of Generic Deep Neural Network Frameworks with Log-supermodular CRFs

Hao Xiong · Yangxiao Lu · Nicholas Ruozzi

SnAKe: Bayesian Optimization with Pathwise Exploration

Jose Pablo Folch · Shiqiang Zhang · Robert Lee · Behrang Shafei · David Walz · Calvin Tsay · Mark van der Wilk · Ruth Misener

On Measuring Excess Capacity in Neural Networks

Florian Graf · Sebastian Zeng · Bastian Rieck · Marc Niethammer · Roland Kwitt

Robust Reinforcement Learning using Offline Data

Kishan Panaganti · Zaiyan Xu · Dileep Kalathil · Mohammad Ghavamzadeh

Thinned random measures for sparse graphs with overlapping communities

Federica Zoe Ricci · Michele Guindani · Erik Sudderth

Value Function Decomposition for Iterative Design of Reinforcement Learning Agents

James MacGlashan · Evan Archer · Alisa Devlic · Takuma Seno · Craig Sherstan · Peter Wurman · Peter Stone

The Privacy Onion Effect: Memorization is Relative

Nicholas Carlini · Matthew Jagielski · Chiyuan Zhang · Nicolas Papernot · Andreas Terzis · Florian Tramer

Evaluating Graph Generative Models with Contrastively Learned Features

Hamed Shirzad · Kaveh Hassani · Danica J. Sutherland

Weakly supervised causal representation learning

Johann Brehmer · Pim de Haan · Phillip Lippe · Taco Cohen

Kernel Memory Networks: A Unifying Framework for Memory Modeling

Georgios Iatropoulos · Johanni Brea · Wulfram Gerstner

Wavelet Score-Based Generative Modeling

Florentin Guth · Simon Coste · Valentin De Bortoli · Stephane Mallat

Monte Carlo Tree Descent for Black-Box Optimization

Yaoguang Zhai · Sicun Gao

Adaptive Sampling for Discovery

Ziping Xu · Eunjae Shim · Ambuj Tewari · Paul Zimmerman

Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data

Nabeel Seedat · Jonathan Crabbé · Ioana Bica · Mihaela van der Schaar

Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis

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

Deep Hierarchical Planning from Pixels

Danijar Hafner · Kuang-Huei Lee · Ian Fischer · Pieter Abbeel

Private Multiparty Perception for Navigation

Hui Lu · Mia Chiquier · Carl Vondrick

Mesoscopic modeling of hidden spiking neurons

Shuqi Wang · Valentin Schmutz · Guillaume Bellec · Wulfram Gerstner

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

Juliette MILLET · Charlotte Caucheteux · pierre orhan · Yves Boubenec · Alexandre Gramfort · Ewan Dunbar · Christophe Pallier · Jean-Remi King

Harmonizing the object recognition strategies of deep neural networks with humans

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

Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning

Aniket Didolkar · Kshitij Gupta · Anirudh Goyal · Nitesh Bharadwaj Gundavarapu · Alex Lamb · Nan Rosemary Ke · Yoshua Bengio

Efficient Training of Low-Curvature Neural Networks

Suraj Srinivas · Kyle Matoba · Himabindu Lakkaraju · François Fleuret

Consistent Sufficient Explanations and Minimal Local Rules for explaining the decision of any classifier or regressor

Salim I. Amoukou · Nicolas Brunel

Social-Inverse: Inverse Decision-making of Social Contagion Management with Task Migrations

Guangmo Tong

Nonlinear Sufficient Dimension Reduction with a Stochastic Neural Network

SIQI LIANG · Yan Sun · Faming Liang

Data-Driven Conditional Robust Optimization

Abhilash Reddy Chenreddy · Nymisha Bandi · Erick Delage

Subgame Solving in Adversarial Team Games

Brian Zhang · Luca Carminati · Federico Cacciamani · Gabriele Farina · Pierriccardo Olivieri · Nicola Gatti · Tuomas Sandholm

Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions

Jiafan He · Dongruo Zhou · Tong Zhang · Quanquan Gu

Universal Rates for Interactive Learning

Steve Hanneke · Amin Karbasi · Shay Moran · Grigoris Velegkas

Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction

Kaifeng Lyu · Zhiyuan Li · Sanjeev Arora

Learning from Label Proportions by Learning with Label Noise

Jianxin Zhang · Yutong Wang · Clay Scott

Efficient Methods for Non-stationary Online Learning

Peng Zhao · Yan-Feng Xie · Lijun Zhang · Zhi-Hua Zhou

Black-Box Generalization: Stability of Zeroth-Order Learning

Konstantinos Nikolakakis · Farzin Haddadpour · Dionysis Kalogerias · Amin Karbasi

Provably Efficient Offline Multi-agent Reinforcement Learning via Strategy-wise Bonus

Qiwen Cui · Simon Du

Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model

Gen Li · Yuejie Chi · Yuting Wei · Yuxin Chen

Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks

Shuoguang Yang · Xuezhou Zhang · Mengdi Wang

VaiPhy: a Variational Inference Based Algorithm for Phylogeny

Hazal Koptagel · Oskar Kviman · Harald Melin · Negar Safinianaini · Jens Lagergren

Local-Global MCMC kernels: the best of both worlds

Sergey Samsonov · Evgeny Lagutin · Marylou Gabrié · Alain Durmus · Alexey Naumov · Eric Moulines

Posterior Matching for Arbitrary Conditioning

Ryan Strauss · Junier B Oliva

FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting

Tian Zhou · Ziqing MA · xue wang · Qingsong Wen · Liang Sun · Tao Yao · Wotao Yin · Rong Jin

LiteTransformerSearch: Training-free Neural Architecture Search for Efficient Language Models

Mojan Javaheripi · Gustavo de Rosa · Subhabrata Mukherjee · Shital Shah · Tomasz Religa · Caio Cesar Teodoro Mendes · Sebastien Bubeck · Farinaz Koushanfar · Debadeepta Dey

Rare Gems: Finding Lottery Tickets at Initialization

Kartik Sreenivasan · Jy-yong Sohn · Liu Yang · Matthew Grinde · Alliot Nagle · Hongyi Wang · Eric Xing · Kangwook Lee · Dimitris Papailiopoulos

Rethinking the compositionality of point clouds through regularization in the hyperbolic space

Antonio Montanaro · Diego Valsesia · Enrico Magli

QC-StyleGAN - Quality Controllable Image Generation and Manipulation

Dat Viet Thanh Nguyen · Phong Tran The · Tan M. Dinh · Cuong Pham · Anh Tran

Look Around and Refer: 2D Synthetic Semantics Knowledge Distillation for 3D Visual Grounding

Eslam Bakr · Yasmeen Alsaedy · Mohamed Elhoseiny

Fine-Grained Semantically Aligned Vision-Language Pre-Training

Juncheng Li · XIN HE · Longhui Wei · Long Qian · Linchao Zhu · Lingxi Xie · Yueting Zhuang · Qi Tian · Siliang Tang

Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition

Yifan Zhang · Bryan Hooi · Lanqing Hong · Jiashi Feng

Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning

Yanpeng Sun · Qiang Chen · Xiangyu He · Jian Wang · Haocheng Feng · Junyu Han · Errui Ding · Jian Cheng · Zechao Li · Jingdong Wang

SageMix: Saliency-Guided Mixup for Point Clouds

Sanghyeok Lee · Minkyu Jeon · Injae Kim · Yunyang Xiong · Hyunwoo Kim

Local Spatiotemporal Representation Learning for Longitudinally-consistent Neuroimage Analysis

Mengwei Ren · Neel Dey · Martin Styner · Kelly Botteron · Guido Gerig

Decomposing NeRF for Editing via Feature Field Distillation

Sosuke Kobayashi · Eiichi Matsumoto · Vincent Sitzmann

Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection

GE ZHANG · Zhenyu Yang · Jia Wu · Jian Yang · Shan Xue · Hao Peng · Jianlin Su · Chuan Zhou · Quan Z. Sheng · Leman Akoglu · Charu Aggarwal

Effective Adaptation in Multi-Task Co-Training for Unified Autonomous Driving

Xiwen Liang · Yangxin Wu · Jianhua Han · Hang Xu · Chunjing XU · Xiaodan Liang

Hierarchical Normalization for Robust Monocular Depth Estimation

Chi Zhang · Wei Yin · Billzb Wang · Gang Yu · BIN FU · Chunhua Shen

GLIPv2: Unifying Localization and Vision-Language Understanding

Haotian Zhang · Pengchuan Zhang · Xiaowei Hu · Yen-Chun Chen · Liunian Li · Xiyang Dai · Lijuan Wang · Lu Yuan · Jenq-Neng Hwang · Jianfeng Gao

AVLEN: Audio-Visual-Language Embodied Navigation in 3D Environments

Sudipta Paul · Amit Roy-Chowdhury · Anoop Cherian

Single-phase deep learning in cortico-cortical networks

Will Greedy · Heng Wei Zhu · Joseph Pemberton · Jack Mellor · Rui Ponte Costa

Understanding Robust Learning through the Lens of Representation Similarities

Christian Cianfarani · Arjun Nitin Bhagoji · Vikash Sehwag · Ben Zhao · Heather Zheng · Prateek Mittal

EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization

Laurent Condat · Kai Yi · Peter Richtarik

LST: Ladder Side-Tuning for Parameter and Memory Efficient Transfer Learning

Yi-Lin Sung · Jaemin Cho · Mohit Bansal

Scalable Neural Video Representations with Learnable Positional Features

Subin Kim · Sihyun Yu · Jaeho Lee · Jinwoo Shin

Are All Losses Created Equal: A Neural Collapse Perspective

Jinxin Zhou · Chong You · Xiao Li · Kangning Liu · Sheng Liu · Qing Qu · Zhihui Zhu

Lazy and Fast Greedy MAP Inference for Determinantal Point Process

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

Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor

Lijun Zhang · Wei Jiang · Jinfeng Yi · Tianbao Yang

Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean Estimation

Kristian Georgiev · Samuel Hopkins

Fast Bayesian Coresets via Subsampling and Quasi-Newton Refinement

Cian Naik · Judith Rousseau · Trevor Campbell

Biological Learning of Irreducible Representations of Commuting Transformations

Alexander Genkin · David Lipshutz · Siavash Golkar · Tiberiu Tesileanu · Dmitri Chklovskii

When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning

Annie Xie · Fahim Tajwar · Archit Sharma · Chelsea Finn

PALMER: Perception - Action Loop with Memory for Long-Horizon Planning

Onur Beker · Mohammad Mohammadi · Amir Zamir

Training Subset Selection for Weak Supervision

Hunter Lang · Aravindan Vijayaraghavan · David Sontag

Contrastive Learning as Goal-Conditioned Reinforcement Learning

Benjamin Eysenbach · Tianjun Zhang · Sergey Levine · Russ Salakhutdinov

CyCLIP: Cyclic Contrastive Language-Image Pretraining

Shashank Goel · Hritik Bansal · Sumit Bhatia · Ryan Rossi · Vishwa Vinay · Aditya Grover

Tempo: Accelerating Transformer-Based Model Training through Memory Footprint Reduction

Muralidhar Andoorveedu · Zhanda Zhu · Bojian Zheng · Gennady Pekhimenko

Trading off Utility, Informativeness, and Complexity in Emergent Communication

Mycal Tucker · Roger Levy · Julie Shah · Noga Zaslavsky

Reduced Representation of Deformation Fields for Effective Non-rigid Shape Matching

Ramana Subramanyam Sundararaman · Riccardo Marin · Emanuele Rodolà · Maks Ovsjanikov

Revisiting Neural Scaling Laws in Language and Vision

Ibrahim Alabdulmohsin · Behnam Neyshabur · Xiaohua Zhai

FourierFormer: Transformer Meets Generalized Fourier Integral Theorem

Tan Nguyen · Minh Pham · Tam Nguyen · Khai Nguyen · Stanley Osher · Nhat Ho

Real-Valued Backpropagation is Unsuitable for Complex-Valued Neural Networks

Zhi-Hao Tan · Yi Xie · Yuan Jiang · Zhi-Hua Zhou

Enhanced Bilevel Optimization via Bregman Distance

Feihu Huang · Junyi Li · Shangqian Gao · Heng Huang

Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based Model

Zhisheng Xiao · Tian Han

Learning Robust Rule Representations for Abstract Reasoning via Internal Inferences

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

Saliency-Aware Neural Architecture Search

Ramtin Hosseini · Pengtao Xie

Training with More Confidence: Mitigating Injected and Natural Backdoors During Training

Zhenting Wang · Hailun Ding · Juan Zhai · Shiqing Ma

First is Better Than Last for Language Data Influence

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

When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment

Zhijing Jin · Sydney Levine · Fernando Gonzalez Adauto · Ojasv Kamal · Maarten Sap · Mrinmaya Sachan · Rada Mihalcea · Josh Tenenbaum · Bernhard Schölkopf

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

Jin Xu · Xiaojiang Liu · Jianhao Yan · Deng Cai · Huayang Li · Jian Li

A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal

Yaqian Zhang · Bernhard Pfahringer · Eibe Frank · Albert Bifet · Nick Jin Sean Lim · Yunzhe Jia

Maximum Likelihood Training of Implicit Nonlinear Diffusion Model

Dongjun Kim · Byeonghu Na · Se Jung Kwon · Dongsoo Lee · Wanmo Kang · Il-chul Moon

On Divergence Measures for Bayesian Pseudocoresets

Balhae Kim · Jungwon Choi · Seanie Lee · Yoonho Lee · Jung-Woo Ha · Juho Lee

Towards Practical Few-shot Query Sets: Transductive Minimum Description Length Inference

Ségolène Martin · Malik Boudiaf · Emilie Chouzenoux · Jean-Christophe Pesquet · Ismail Ayed

MABSplit: Faster Forest Training Using Multi-Armed Bandits

Mo Tiwari · Ryan Kang · Jaeyong Lee · Chris Piech · Ilan Shomorony · Sebastian Thrun · Martin Zhang

Reconstructing Training Data From Trained Neural Networks

Niv Haim · Gal Vardi · Gilad Yehudai · Ohad Shamir · Michal Irani

Information-Theoretic Safe Exploration with Gaussian Processes

Alessandro Bottero · Carlos Luis · Julia Vinogradska · Felix Berkenkamp · Jan Peters

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

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

End-to-end Algorithm Synthesis with Recurrent Networks: Extrapolation without Overthinking

Arpit Bansal · Avi Schwarzschild · Eitan Borgnia · Zeyad Emam · Furong Huang · Micah Goldblum · Tom Goldstein

Conformal Prediction with Temporal Quantile Adjustments

Zhen Lin · Shubhendu Trivedi · Jimeng Sun

Expected Frequency Matrices of Elections: Computation, Geometry, and Preference Learning

Niclas Boehmer · Robert Bredereck · Edith Elkind · Piotr Faliszewski · Stanisław Szufa

Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination

Masaki Adachi · Satoshi Hayakawa · Martin Jørgensen · Harald Oberhauser · Michael A Osborne

Online PAC-Bayes Learning

Maxime Haddouche · Benjamin Guedj

On the inability of Gaussian process regression to optimally learn compositional functions

Matteo Giordano · Kolyan Ray · Johannes Schmidt-Hieber

Online Agnostic Multiclass Boosting

Vinod Raman · Ambuj Tewari

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

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

Efficient Submodular Optimization under Noise: Local Search is Robust

Lingxiao Huang · Yuyi Wang · Chunxue Yang · Huanjian Zhou

Adversarially Robust Learning: A Generic Minimax Optimal Learner and Characterization

Omar Montasser · Steve Hanneke · Nati Srebro

A Regret-Variance Trade-Off in Online Learning

Dirk van der Hoeven · Nikita Zhivotovskiy · Nicolò Cesa-Bianchi

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

Itay Safran · Gal Vardi · Jason Lee

Off-Policy Evaluation for Episodic Partially Observable Markov Decision Processes under Non-Parametric Models

Rui Miao · Zhengling Qi · Xiaoke Zhang

Probabilistic Missing Value Imputation for Mixed Categorical and Ordered Data

Yuxuan Zhao · Alex Townsend · Madeleine Udell

Double Bubble, Toil and Trouble: Enhancing Certified Robustness through Transitivity

Andrew Cullen · Paul Montague · Shijie Liu · Sarah Erfani · Benjamin Rubinstein

Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain Generalization

Devansh Arpit · Huan Wang · Yingbo Zhou · Caiming Xiong

Coresets for Vertical Federated Learning: Regularized Linear Regression and $K$-Means Clustering

Lingxiao Huang · Zhize Li · Jialin Sun · Haoyu Zhao

Active Bayesian Causal Inference

Christian Toth · Lars Lorch · Christian Knoll · Andreas Krause · Franz Pernkopf · Robert Peharz · Julius von Kügelgen

All Politics is Local: Redistricting via Local Fairness

Shao-Heng Ko · Erin Taylor · Pankaj Agarwal · Kamesh Munagala

Sequence Model Imitation Learning with Unobserved Contexts

Gokul Swamy · Sanjiban Choudhury · J. Bagnell · Steven Wu

Anticipating Performativity by Predicting from Predictions

Celestine Mendler-Dünner · Frances Ding · Yixin Wang

Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks

Arian Jamasb · Ramon Viñas Torné · Eric Ma · Yuanqi Du · Charles Harris · Kexin Huang · Dominic Hall · Pietro Lió · Tom Blundell

The computational and learning benefits of Daleian neural networks

Adam Haber · Elad Schneidman

Optimal Algorithms for Decentralized Stochastic Variational Inequalities

Dmitry Kovalev · Aleksandr Beznosikov · Abdurakhmon Sadiev · Michael Persiianov · Peter Richtarik · Alexander Gasnikov

Theory and Approximate Solvers for Branched Optimal Transport with Multiple Sources

Peter Lippmann · Enrique Fita Sanmartín · Fred Hamprecht

Algorithms with Prediction Portfolios

Michael Dinitz · Sungjin Im · Thomas Lavastida · Benjamin Moseley · Sergei Vassilvitskii

Logical Activation Functions: Logit-space equivalents of Probabilistic Boolean Operators

Scott Lowe · Robert Earle · Jason d'Eon · Thomas Trappenberg · Sageev Oore

Understanding the Eluder Dimension

Gene Li · Pritish Kamath · Dylan J Foster · Nati Srebro

A Projection-free Algorithm for Constrained Stochastic Multi-level Composition Optimization

Tesi Xiao · Krishnakumar Balasubramanian · Saeed Ghadimi

Robust Model Selection and Nearly-Proper Learning for GMMs

Allen Liu · Jerry Li · Ankur Moitra

On Gap-dependent Bounds for Offline Reinforcement Learning

Xinqi Wang · Qiwen Cui · Simon Du

Perfect Sampling from Pairwise Comparisons

Dimitris Fotakis · Alkis Kalavasis · Christos Tzamos

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

Benjamin Dubois-Taine · Francis Bach · Quentin Berthet · Adrien Taylor

Finding Correlated Equilibrium of Constrained Markov Game: A Primal-Dual Approach

Ziyi Chen · Shaocong Ma · Yi Zhou

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

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

Provably expressive temporal graph networks

Amauri Souza · Diego Mesquita · Samuel Kaski · Vikas Garg

What's the Harm? Sharp Bounds on the Fraction Negatively Affected by Treatment

Nathan Kallus

Dynamic Fair Division with Partial Information

Gerdus Benade · Daniel Halpern · Alexandros Psomas

On Computing Probabilistic Explanations for Decision Trees

Marcelo Arenas · Pablo Barceló · Miguel Romero Orth · Bernardo Subercaseaux

Anonymized Histograms in Intermediate Privacy Models

Badih Ghazi · Pritish Kamath · Ravi Kumar · Pasin Manurangsi

List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering

Ilias Diakonikolas · Daniel Kane · Sushrut Karmalkar · Ankit Pensia · Thanasis Pittas

The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization

Dmitry Kovalev · Alexander Gasnikov

Near-Optimal Sample Complexity Bounds for Constrained MDPs

Sharan Vaswani · Lin Yang · Csaba Szepesvari

Verification and search algorithms for causal DAGs

Davin Choo · Kirankumar Shiragur · Arnab Bhattacharyya

Learning and Covering Sums of Independent Random Variables with Unbounded Support

Alkis Kalavasis · Konstantinos Stavropoulos · Emmanouil Zampetakis

Fast Mixing of Stochastic Gradient Descent with Normalization and Weight Decay

Zhiyuan Li · Tianhao Wang · Dingli Yu

Robust Testing in High-Dimensional Sparse Models

Anand Jerry George · Clément L Canonne

Dynamic Tensor Product Regression

Aravind Reddy · Zhao Song · Lichen Zhang

Semi-supervised Active Linear Regression

Nived Rajaraman · Fnu Devvrit · Pranjal Awasthi

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

Tongyang Li · Ruizhe Zhang

Independence Testing for Bounded Degree Bayesian Networks

Arnab Bhattacharyya · Clément L Canonne · Qiping Yang

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

Oren Mangoubi · Nisheeth Vishnoi

Context-Based Dynamic Pricing with Partially Linear Demand Model

Jinzhi Bu · David Simchi-Levi · Chonghuan Wang

Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods

Kimon Antonakopoulos · Ali Kavis · Volkan Cevher

Neural Lyapunov Control of Unknown Nonlinear Systems with Stability Guarantees

Ruikun Zhou · Thanin Quartz · Hans De Sterck · Jun Liu

Causal Inference with Non-IID Data using Linear Graphical Models

Chi Zhang · Karthika Mohan · Judea Pearl

Submodular Maximization in Clean Linear Time

Wenxin Li · Moran Feldman · Ehsan Kazemi · Amin Karbasi

Continuously Tempered PDMP samplers

Matthew Sutton · Robert Salomone · Augustin Chevallier · Paul Fearnhead

Regret Bounds for Multilabel Classification in Sparse Label Regimes

Róbert Busa-Fekete · Heejin Choi · Krzysztof Dembczynski · Claudio Gentile · Henry Reeve · Balazs Szorenyi

Provable Benefit of Multitask Representation Learning in Reinforcement Learning

Yuan Cheng · Songtao Feng · Jing Yang · Hong Zhang · Yingbin Liang

BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression

Haoyu Zhao · Boyue Li · Zhize Li · Peter Richtarik · Yuejie Chi

Incrementality Bidding via Reinforcement Learning under Mixed and Delayed Rewards

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

DataMUX: Data Multiplexing for Neural Networks

Vishvak Murahari · Carlos Jimenez · Runzhe Yang · Karthik Narasimhan

Adaptively Exploiting d-Separators with Causal Bandits

Blair Bilodeau · Linbo Wang · Dan Roy

Spending Thinking Time Wisely: Accelerating MCTS with Virtual Expansions

Weirui Ye · Pieter Abbeel · Yang Gao

Toward Efficient Robust Training against Union of $\ell_p$ Threat Models

Gaurang Sriramanan · Maharshi Gor · Soheil Feizi

Inverse Game Theory for Stackelberg Games: the Blessing of Bounded Rationality

Jibang Wu · Weiran Shen · Fei Fang · Haifeng Xu

Global Normalization for Streaming Speech Recognition in a Modular Framework

Ehsan Variani · Ke Wu · Michael D Riley · David Rybach · Matt Shannon · Cyril Allauzen

Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline

Penghao Wu · Xiaosong Jia · Li Chen · Junchi Yan · Hongyang Li · Yu Qiao

DeepInteraction: 3D Object Detection via Modality Interaction

Zeyu Yang · Jiaqi Chen · Zhenwei Miao · Wei Li · Xiatian Zhu · Li Zhang

Category-Level 6D Object Pose Estimation in the Wild: A Semi-Supervised Learning Approach and A New Dataset

Yanjie Ze · Xiaolong Wang

Planning for Sample Efficient Imitation Learning

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

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

Markus Hiller · Mehrtash Harandi · Tom Drummond

Polynomial Neural Fields for Subband Decomposition and Manipulation

Guandao Yang · Sagie Benaim · Varun Jampani · Kyle Genova · Jonathan Barron · Thomas Funkhouser · Bharath Hariharan · Serge Belongie

Improving Self-Supervised Learning by Characterizing Idealized Representations

Yann Dubois · Stefano Ermon · Tatsunori Hashimoto · Percy Liang

Deep Ensembles Work, But Are They Necessary?

Taiga Abe · Estefany Kelly Buchanan · Geoff Pleiss · Richard Zemel · John Cunningham

Learning to Mitigate AI Collusion on Economic Platforms

Gianluca Brero · Eric Mibuari · Nicolas Lepore · David Parkes

Hamiltonian Latent Operators for content and motion disentanglement in image sequences

Asif Khan · Amos Storkey

Posterior Collapse of a Linear Latent Variable Model

Zihao Wang · Liu Ziyin

TREC: Transient Redundancy Elimination-based Convolution

Jiawei Guan · Feng Zhang · Jiesong Liu · Hsin-Hsuan Sung · Ruofan Wu · Xiaoyong Du · Xipeng Shen

Unsupervised Reinforcement Learning with Contrastive Intrinsic Control

Michael Laskin · Hao Liu · Xue Bin Peng · Denis Yarats · Aravind Rajeswaran · Pieter Abbeel

Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional Networks

Renan A. Rojas-Gomez · Teck-Yian Lim · Alex Schwing · Minh Do · Raymond A. Yeh

Unsupervised Cross-Task Generalization via Retrieval Augmentation

Bill Yuchen Lin · Kangmin Tan · Chris Miller · Beiwen Tian · Xiang Ren

Self-Supervised Learning Through Efference Copies

Franz Scherr · Qinghai Guo · Timoleon Moraitis

Aligning individual brains with fused unbalanced Gromov Wasserstein

Alexis Thual · Quang Huy TRAN · Tatiana Zemskova · Nicolas Courty · Rémi Flamary · Stanislas Dehaene · Bertrand Thirion

Formalizing Consistency and Coherence of Representation Learning

Harald Strömfelt · Luke Dickens · Artur Garcez · Alessandra Russo

Non-deep Networks

Ankit Goyal · Alexey Bochkovskiy · Jia Deng · Vladlen Koltun

Mining Unseen Classes via Regional Objectness: A Simple Baseline for Incremental Segmentation

Zekang Zhang · Guangyu Gao · Zhiyuan Fang · Jianbo Jiao · Yunchao Wei

Class-Dependent Label-Noise Learning with Cycle-Consistency Regularization

De Cheng · Yixiong Ning · Nannan Wang · Xinbo Gao · Heng Yang · Yuxuan Du · Bo Han · Tongliang Liu

Solving Quantitative Reasoning Problems with Language Models

Aitor Lewkowycz · Anders Andreassen · David Dohan · Ethan Dyer · Henryk Michalewski · Vinay Ramasesh · Ambrose Slone · Cem Anil · Imanol Schlag · Theo Gutman-Solo · Yuhuai Wu · Behnam Neyshabur · Guy Gur-Ari · Vedant Misra

GENIE: Higher-Order Denoising Diffusion Solvers

Tim Dockhorn · Arash Vahdat · Karsten Kreis

Estimating the Arc Length of the Optimal ROC Curve and Lower Bounding the Maximal AUC

Song Liu

Marksman Backdoor: Backdoor Attacks with Arbitrary Target Class

Khoa D Doan · Yingjie Lao · Ping Li

Fuzzy Learning Machine

Junbiao Cui · Jiye Liang

Second Thoughts are Best: Learning to Re-Align With Human Values from Text Edits

Ruibo Liu · Chenyan Jia · Ge Zhang · Ziyu Zhuang · Tony Liu · Soroush Vosoughi

Grounded Video Situation Recognition

Zeeshan Khan · C.V. Jawahar · Makarand Tapaswi

Robust Neural Posterior Estimation and Statistical Model Criticism

Daniel Ward · Patrick Cannon · Mark Beaumont · Matteo Fasiolo · Sebastian Schmon

RAMBO-RL: Robust Adversarial Model-Based Offline Reinforcement Learning

Marc Rigter · Bruno Lacerda · Nick Hawes

Instance-based Learning for Knowledge Base Completion

Wanyun Cui · Xingran Chen

Sub-exponential time Sum-of-Squares lower bounds for Principal Components Analysis

Aaron Potechin · Goutham Rajendran

Tight Mutual Information Estimation With Contrastive Fenchel-Legendre Optimization

Qing Guo · Junya Chen · Dong Wang · Yuewei Yang · Xinwei Deng · Jing Huang · Larry Carin · Fan Li · Chenyang Tao

A Rotated Hyperbolic Wrapped Normal Distribution for Hierarchical Representation Learning

Seunghyuk Cho · Juyong Lee · Jaesik Park · Dongwoo Kim

Finding and Listing Front-door Adjustment Sets

Hyunchai Jeong · Jin Tian · Elias Bareinboim

SALSA: Attacking Lattice Cryptography with Transformers

Emily Wenger · Mingjie Chen · Francois Charton · Kristin E. Lauter

Automatic differentiation of nonsmooth iterative algorithms

Jerome Bolte · Edouard Pauwels · Samuel Vaiter

Learning from a Sample in Online Algorithms

C.J. Argue · Alan Frieze · Anupam Gupta · Christopher Seiler

Trajectory of Mini-Batch Momentum: Batch Size Saturation and Convergence in High Dimensions

Kiwon Lee · Andrew Cheng · Elliot Paquette · Courtney Paquette

Improved Algorithms for Neural Active Learning

Yikun Ban · Yuheng Zhang · Hanghang Tong · Arindam Banerjee · Jingrui He

Matching in Multi-arm Bandit with Collision

YiRui Zhang · Siwei Wang · Zhixuan Fang

A Spectral Approach to Item Response Theory

Duc Nguyen · Anderson Ye Zhang

JAWS: Auditing Predictive Uncertainty Under Covariate Shift

Drew Prinster · Anqi Liu · Suchi Saria

Bessel Equivariant Networks for Inversion of Transmission Effects in Multi-Mode Optical Fibres

Joshua Mitton · Simon Mekhail · Miles Padgett · Daniele Faccio · Marco Aversa · Roderick Murray-Smith

MetricFormer: A Unified Perspective of Correlation Exploring in Similarity Learning

Jiexi Yan · Erkun Yang · Cheng Deng · Heng Huang

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

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

Learning Recourse on Instance Environment to Enhance Prediction Accuracy

Lokesh N · Guntakanti Sai Koushik · Abir De · Sunita Sarawagi

Spherization Layer: Representation Using Only Angles

Hoyong Kim · kangil kim

Disentangling the Predictive Variance of Deep Ensembles through the Neural Tangent Kernel

Seijin Kobayashi · Pau Vilimelis Aceituno · Johannes von Oswald

Agreement-on-the-line: Predicting the Performance of Neural Networks under Distribution Shift

Christina Baek · Yiding Jiang · Aditi Raghunathan · J. Zico Kolter

Efficient and Stable Fully Dynamic Facility Location

Sayan Bhattacharya · Silvio Lattanzi · Nikos Parotsidis

Coresets for Wasserstein Distributionally Robust Optimization Problems

Ruomin Huang · Jiawei Huang · Wenjie Liu · Hu Ding

Differentially Private Online-to-batch for Smooth Losses

Qinzi Zhang · Hoang Tran · Ashok Cutkosky

How Transferable are Video Representations Based on Synthetic Data?

Yo-whan Kim · Samarth Mishra · SouYoung Jin · Rameswar Panda · Hilde Kuehne · Leonid Karlinsky · Venkatesh Saligrama · Kate Saenko · Aude Oliva · Rogerio Feris

SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles

Chejian Xu · Wenhao Ding · Weijie Lyu · ZUXIN LIU · Shuai Wang · Yihan He · Hanjiang Hu · DING ZHAO · Bo Li

GLOBEM Dataset: Multi-Year Datasets for Longitudinal Human Behavior Modeling Generalization

Xuhai Xu · Han Zhang · Yasaman Sefidgar · Yiyi Ren · Xin Liu · Woosuk Seo · Jennifer Brown · Kevin Kuehn · Mike Merrill · Paula Nurius · Shwetak Patel · Tim Althoff · Margaret Morris · Eve Riskin · Jennifer Mankoff · Anind Dey

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

Alex Tamkin · Gaurab Banerjee · Mohamed Owda · Vincent Liu · Shashank Rammoorthy · Noah Goodman

GOOD: A Graph Out-of-Distribution Benchmark

Shurui Gui · Xiner Li · Limei Wang · Shuiwang Ji

AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection

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

MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge

Linxi Fan · Guanzhi Wang · Yunfan Jiang · Ajay Mandlekar · Yuncong Yang · Haoyi Zhu · Andrew Tang · De-An Huang · Yuke Zhu · Anima Anandkumar

EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine

Jiayi Weng · Min Lin · Shengyi Huang · Bo Liu · Denys Makoviichuk · Viktor Makoviychuk · Zichen Liu · Yufan Song · Ting Luo · Yukun Jiang · Zhongwen Xu · Shuicheng Yan

DART: Articulated Hand Model with Diverse Accessories and Rich Textures

Daiheng Gao · Yuliang Xiu · Kailin Li · Lixin Yang · Feng Wang · Peng Zhang · Bang Zhang · Cewu Lu · Ping Tan

HandMeThat: Human-Robot Communication in Physical and Social Environments

Yanming Wan · Jiayuan Mao · Josh Tenenbaum

The Dollar Street Dataset: Images Representing the Geographic and Socioeconomic Diversity of the World

William Gaviria Rojas · Sudnya Diamos · Keertan Kini · David Kanter · Vijay Janapa Reddi · Cody Coleman

PulseImpute: A Novel Benchmark Task for Pulsative Physiological Signal Imputation

Maxwell Xu · Alexander Moreno · Supriya Nagesh · Varol Aydemir · David Wetter · Santosh Kumar · James Rehg

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

Abishek Thangamuthu · Gunjan Kumar · Suresh Bishnoi · Ravinder Bhattoo · N M Anoop Krishnan · Sayan Ranu

Enabling Detailed Action Recognition Evaluation Through Video Dataset Augmentation

Jihoon Chung · Yu Wu · Olga Russakovsky

Multi-LexSum: Real-world Summaries of Civil Rights Lawsuits at Multiple Granularities

Zejiang Shen · Kyle Lo · Lauren Yu · Nathan Dahlberg · Margo Schlanger · Doug Downey

SurDis: A Surface Discontinuity Dataset for Wearable Technology to Assist Blind Navigation in Urban Environments

Kuan Yew Leong · Siew Mooi Lim

Ontologue: Declarative Benchmark Construction for Ontological Multi-Label Classification

Sean Yang · Bernease Herman · Bill Howe

StrokeRehab: A Benchmark Dataset for Sub-second Action Identification

Aakash Kaku · Kangning Liu · Avinash Parnandi · Haresh Rengaraj Rajamohan · Kannan Venkataramanan · Anita Venkatesan · Audre Wirtanen · Natasha Pandit · Heidi Schambra · Carlos Fernandez-Granda

A new dataset for multilingual keyphrase generation

Frédéric Piedboeuf · Philippe Langlais

Communicating Natural Programs to Humans and Machines

Sam Acquaviva · Yewen Pu · Marta Kryven · Theodoros Sechopoulos · Catherine Wong · Gabrielle Ecanow · Maxwell Nye · Michael Tessler · Josh Tenenbaum

ComMU: Dataset for Combinatorial Music Generation

Hyun Lee · Taehyun Kim · Hyolim Kang · Minjoo Ki · Hyeonchan Hwang · kwanho park · Sharang Han · Seon Joo Kim

The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset

Hugo Laurençon · Lucile Saulnier · Thomas Wang · Christopher Akiki · Albert Villanova del Moral · Teven Le Scao · Leandro Von Werra · Chenghao Mou · Eduardo González Ponferrada · Huu Nguyen · Jörg Frohberg · Mario Šaško · Quentin Lhoest · Angelina McMillan-Major · Gerard Dupont · Stella Biderman · Anna Rogers · Loubna Ben allal · Francesco De Toni · Giada Pistilli · Olivier Nguyen · Somaieh Nikpoor · Maraim Masoud · Pierre Colombo · Javier de la Rosa · Paulo Villegas · Tristan Thrush · Shayne Longpre · Sebastian Nagel · Leon Weber · Manuel Muñoz · Jian Zhu · Daniel Van Strien · Zaid Alyafeai · Khalid Almubarak · Minh Chien Vu · Itziar Gonzalez-Dios · Aitor Soroa · Kyle Lo · Manan Dey · Pedro Ortiz Suarez · Aaron Gokaslan · Shamik Bose · David Adelani · Long Phan · Hieu Tran · Ian Yu · Suhas Pai · Jenny Chim · Violette Lepercq · Suzana Ilic · Margaret Mitchell · Sasha Alexandra Luccioni · Yacine Jernite

This is the way: designing and compiling LEPISZCZE, a comprehensive NLP benchmark for Polish

Lukasz Augustyniak · Kamil Tagowski · Albert Sawczyn · Denis Janiak · Roman Bartusiak · Adrian Szymczak · Arkadiusz Janz · Piotr Szymański · Marcin Wątroba · Mikołaj Morzy · Tomasz Kajdanowicz · Maciej Piasecki

Flare7K: A Phenomenological Nighttime Flare Removal Dataset

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

Online Nonnegative CP-dictionary Learning for Markovian Data

Hanbaek Lyu · Christopher Strohmeier · Deanna Needell

Supervised Dimensionality Reduction and Visualization using Centroid-Encoder

Tomojit Ghosh · Michael Kirby

Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization

Feihu Huang · Shangqian Gao · Jian Pei · Heng Huang

Joint Estimation and Inference for Data Integration Problems based on Multiple Multi-layered Gaussian Graphical Models

Subhabrata Majumdar · George Michailidis

[Re] Explaining in Style: Training a GAN to explain a classifier in StyleSpace

Noah van der Vleuten · Tadija Radusinović · Rick Akkerman · Meilina Reksoprodjo

[Re] Replication Study of DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks

Velizar Shulev · Paul Verhagen · Shuai Wang · Jennifer Zhuge

[Re] Value Alignment Verification

Siba Smarak Panigrahi · Sohan Patnaik

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NeurIPS 2022 Competition Track: Overview & Results

Marco Ciccone · Gustavo Stolovitzky · Jake Albrecht

6:00 PM - 8:00 PM

An introduction by Isabelle Guyon and Evelyne Viegas followed by posters presentations of competition results with the main organizers.

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ML Safety NeurIPS Social

David Krueger · Orpheus Lummis · Joshua Clymer

6:00 PM - 8:00 PM

As ML systems increase in capabilities and integration in society, their safety and alignment grow in importance. We welcome participants interested in or working on AI safety topics for a semi-structured social meetup at NeurIPS 2022. Meet peers who may have read your papers or authors you've read, and build new friendships and collaboration opportunities. We recommend using Swapcard, to request one-one-one meetings with other attendants. Example topics include "Establishing trust in advanced AI systems," "Concrete Threat Models," and "AI Governance and Policy", "Model interpretability", ...

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NeurIPS 2022 Space & ML Social Event

Jodie Hughes

6:00 PM - 8:00 PM

The NeurIPS 2022 Space & ML social will kick off with an opening lighting round of callbacks, where guests can make their brief case for the potential of ML on (but not limited to) areas such as the following: climate change (predicting wildfires, preventing floods), space exploration, early event detection and situational awareness, fairness and equity in algorithmic decision-making, or open-source science. Following this lightning round, we will organize a social experience for attendees to meet each other and foster co-opetition (cooperative competition) in a space pub quiz, with special guests from our space industry partners (NASA, US Department of Energy, ESA, Australia Space Agency, etc).

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RL Social

Yuxi Li · Omer Gottesman · Niranjani Prasad

6:00 PM - 8:00 PM

The purpose of this social is to provide an opportunity for the researchers in the RL community, both young and senior, and from both industry and academia to interact, meet each other and exchange ideas. In particular, we the organizers will invite RL experts from the many sub-areas of RL to attend and provide younger researchers with the opportunity to meet them and discuss any topics which might be of interest in their research and career.

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Ethics Review - Open Discussion

Deborah Raji · William Isaac · Cherie Poland · Alexandra Luccioni

6:00 PM - 8:00 PM

Ethical review has become an intrinsic part of the NeurIPS review process, but many unanswered question remain around topics such as: the role of ethics review; current and potential future ethical issues (consent, privacy, copyright); ethics awareness/visibility (e.g. how to help technical reviewers with access to resources to adequately flag ethical issues in papers), etc. We will start the townhall with a brief panel discussions and then open up the floor to community input/feedback and answer any questions that audience members will have.

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