UniDoc: Unified Pretraining Framework for Document Understanding Jiuxiang Gu, Jason Kuen, Vlad I Morariu, Handong Zhao, Rajiv Jain, Nikolaos Barmpalios, Ani Nenkova, Tong Sun

Counterfactual Explanations Can Be Manipulated Dylan Slack, Anna Hilgard, Himabindu Lakkaraju, Sameer Singh

Hyperbolic Busemann Learning with Ideal Prototypes Mina Ghadimi Atigh, Martin Keller-Ressel, Pascal Mettes

Backward-Compatible Prediction Updates: A Probabilistic Approach Frederik Träuble, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Peter V. Gehler

Truncated Marginal Neural Ratio Estimation Benjamin K Miller, Alex Cole, Patrick Forré, Gilles Louppe, Christoph Weniger

Non-local Latent Relation Distillation for Self-Adaptive 3D Human Pose Estimation Jogendra Nath Kundu, Siddharth Seth, Anirudh Jamkhandi, Pradyumna YM, Varun Jampani, Anirban Chakraborty, Venkatesh Babu R

Multimodal Few-Shot Learning with Frozen Language Models Maria Tsimpoukelli, Jacob L Menick, Serkan Cabi, S. M. Ali Eslami, Oriol Vinyals, Felix Hill

AugMax: Adversarial Composition of Random Augmentations for Robust Training Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Anima Anandkumar, Zhangyang Wang

Meta-Learning Reliable Priors in the Function Space Jonas Rothfuss, Dominique Heyn, jinfan Chen, Andreas Krause

VoiceMixer: Adversarial Voice Style Mixup Sang-Hoon Lee, Ji-Hoon Kim, Hyunseung Chung, Seong-Whan Lee

Learning to Select Exogenous Events for Marked Temporal Point Process Ping Zhang, Rishabh Iyer, Ashish Tendulkar, Gaurav Aggarwal, Abir De

DRIVE: One-bit Distributed Mean Estimation Shay Vargaftik, Ran Ben-Basat, Amit Portnoy, Gal Mendelson, Yaniv Ben-Itzhak, Michael Mitzenmacher

Learning Space Partitions for Path Planning Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E Gonzalez, Dan Klein, Yuandong Tian

Local Explanation of Dialogue Response Generation Yi-Lin Tuan, Connor Pryor, Wenhu Chen, Lise Getoor, William Yang Wang

Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj

Numerical influence of ReLU’(0) on backpropagation David Bertoin, Jérôme Bolte, Sébastien Gerchinovitz, Edouard Pauwels

Neighborhood Reconstructing Autoencoders Yonghyeon LEE, Hyeokjun Kwon, Frank Park

TopicNet: Semantic Graph-Guided Topic Discovery Zhibin Duan, Yi.shi Xu, Bo Chen, dongsheng wang, Chaojie Wang, Mingyuan Zhou

The Utility of Explainable AI in Ad Hoc Human-Machine Teaming Rohan Paleja, Muyleng Ghuy, Nadun Ranawaka Arachchige, Reed Jensen, Matthew Gombolay

A Winning Hand: Compressing Deep Networks Can Improve Out-of-Distribution Robustness James Diffenderfer, Brian Bartoldson, Shreya Chaganti, Jize Zhang, Bhavya Kailkhura

Do Different Tracking Tasks Require Different Appearance Models? Zhongdao Wang, Hengshuang Zhao, Ya-Li Li, Shengjin Wang, Philip Torr, Luca Bertinetto

Towards robust vision by multi-task learning on monkey visual cortex Shahd Safarani, Arne Nix, Konstantin Willeke, Santiago Cadena, Kelli Restivo, George Denfield, Andreas Tolias, Fabian H. Sinz

Learning Domain Invariant Representations in Goal-conditioned Block MDPs Beining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael Zhang, Jimmy Ba

Fuzzy Clustering with Similarity Queries Wasim Huleihel, Arya Mazumdar, Soumyabrata Pal

Sample Selection for Fair and Robust Training Yuji Roh, Kangwook Lee, Steven Whang, Changho Suh

NeurWIN: Neural Whittle Index Network For Restless Bandits Via Deep RL Khaled Nakhleh, Santosh Ganji, Ping-Chun Hsieh, I-Hong Hou, Srinivas Shakkottai

Alias-Free Generative Adversarial Networks Tero Karras, Miika Aittala, Samuli Laine, Erik Härkönen, Janne Hellsten, Jaakko Lehtinen, Timo Aila

Continuous Mean-Covariance Bandits Yihan Du, Siwei Wang, Zhixuan Fang, Longbo Huang

Towards Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games Xiangyu Liu, Hangtian Jia, Ying Wen, Yujing Hu, Yingfeng Chen, Changjie Fan, ZHIPENG HU, Yaodong Yang

Global Filter Networks for Image Classification Yongming Rao, Wenliang Zhao, Zheng Zhu, Jiwen Lu, Jie Zhou

Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee Xiaofeng Fan, Yining Ma, Zhongxiang Dai, Wei Jing, Cheston Tan, Bryan Kian Hsiang Low

Compacter: Efficient Low-Rank Hypercomplex Adapter Layers Rabeeh Karimi Mahabadi, James Henderson, Sebastian Ruder

Scaling Neural Tangent Kernels via Sketching and Random Features Amir Zandieh, Insu Han, Haim Avron, Neta Shoham, Chaewon Kim, Jinwoo Shin

Long Short-Term Transformer for Online Action Detection Mingze Xu, Yuanjun Xiong, Hao Chen, Xinyu Li, Wei Xia, Zhuowen Tu, Stefano Soatto

Near Optimal Policy Optimization via REPS Aldo Pacchiano, Jonathan N Lee, Peter L. Bartlett, Ofir Nachum

Learning Optimal Predictive Checklists Haoran Zhang, Quaid D. Morris, Berk Ustun, Marzyeh Ghassemi

Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs Hyperbolic Atsushi Suzuki, Atsushi Nitanda, jing wang, Linchuan Xu, Kenji Yamanishi, Marc Cavazza

Gradient Starvation: A Learning Proclivity in Neural Networks Mohammad Pezeshki, Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie

Privately Learning Subspaces Vikrant Singhal, Thomas Steinke

On the Value of Interaction and Function Approximation in Imitation Learning Nived Rajaraman, Yanjun Han, Lin Yang, Jingbo Liu, Jiantao Jiao, Kannan Ramchandran

Regularized Softmax Deep Multi-Agent Q-Learning Ling Pan, Tabish Rashid, Bei Peng, Longbo Huang, Shimon Whiteson

Systematic Generalization with Edge Transformers Leon Bergen, Timothy O'Donnell, Dzmitry Bahdanau

TransformerFusion: Monocular RGB Scene Reconstruction using Transformers Aljaz Bozic, Pablo Palafox, Justus Thies, Angela Dai, Matthias Niessner

Adaptive Data Augmentation on Temporal Graphs Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, Siddharth Bhatia, Bryan Hooi

Terra: Imperative-Symbolic Co-Execution of Imperative Deep Learning Programs Taebum Kim, Eunji Jeong, Geon-Woo Kim, Yunmo Koo, Sehoon Kim, Gyeongin Yu, Byung-Gon Chun

Uniform Sampling over Episode Difficulty Sébastien Arnold, Guneet Dhillon, Avinash Ravichandran, Stefano Soatto

Scalable Intervention Target Estimation in Linear Models Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer

Differentiable Unsupervised Feature Selection based on a Gated Laplacian Ofir Lindenbaum, Uri Shaham, Erez Peterfreund, Jonathan Svirsky, Nicolas Casey, Yuval Kluger

A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning Mingde Zhao, Zhen Liu, Sitao Luan, Shuyuan Zhang, Doina Precup, Yoshua Bengio

Beltrami Flow and Neural Diffusion on Graphs Benjamin Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael Bronstein

Think Big, Teach Small: Do Language Models Distil Occam’s Razor? Gonzalo Jaimovitch-Lopez, David Castellano Falcón, Cesar Ferri, José Hernández-Orallo

Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA Hermanni Hälvä, Sylvain Le Corff, Luc Lehéricy, Jonathan So, Yongjie Zhu, Elisabeth Gassiat, Aapo Hyvarinen

Reconstruction for Powerful Graph Representations Leonardo Cotta, Christopher Morris, Bruno Ribeiro

Revealing and Protecting Labels in Distributed Training Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays

Reliable Decisions with Threshold Calibration Roshni Sahoo, Shengjia Zhao, Alyssa Chen, Stefano Ermon

End-to-End Weak Supervision Salva Rühling Cachay, Benedikt Boecking, Artur Dubrawski

Shift Invariance Can Reduce Adversarial Robustness Vasu Singla, Songwei Ge, Basri Ronen, David Jacobs

Replay-Guided Adversarial Environment Design Minqi Jiang, Michael Dennis, Jack Parker-Holder, Jakob Foerster, Edward Grefenstette, Tim Rocktäschel

Efficient Truncated Linear Regression with Unknown Noise Variance Constantinos Daskalakis, Patroklos Stefanou, Rui Yao, Emmanouil Zampetakis

Breaking the Dilemma of Medical Image-to-image Translation Lingke Kong, Chenyu Lian, Detian Huang, zhenjiang li, Yanle Hu, Qichao Zhou

Temporally Abstract Partial Models Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, Doina Precup

Is Automated Topic Model Evaluation Broken? The Incoherence of Coherence Alexander Hoyle, Pranav Goel, Andrew Hian-Cheong, Denis Peskov, Jordan Boyd-Graber, Philip Resnik

Adversarial Attacks on Black Box Video Classifiers: Leveraging the Power of Geometric Transformations Shasha Li, Abhishek Aich, Shitong Zhu, Salman Asif, Chengyu Song, Amit Roy-Chowdhury, Srikanth Krishnamurthy

Inverse-Weighted Survival Games Xintian Han, Mark Goldstein, Aahlad Puli, Thomas Wies, Adler J. Perotte, Rajesh Ranganath

Evolution Gym: A Large-Scale Benchmark for Evolving Soft Robots Jagdeep Bhatia, Holly Jackson, Yunsheng Tian, Jie Xu, Wojciech Matusik

On Calibration and Out-of-Domain Generalization Yoav Wald, Amir Feder, Daniel Greenfeld, Uri Shalit

Circa: Stochastic ReLUs for Private Deep Learning Zahra Ghodsi, Nandan Kumar Jha, Brandon Reagen, Siddharth Garg

Reinforcement Learning in Reward-Mixing MDPs Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor

A Gang of Adversarial Bandits Mark Herbster, Stephen Pasteris, Fabio Vitale, Massimiliano Pontil

Explaining Hyperparameter Optimization via Partial Dependence Plots Julia Moosbauer, Julia Herbinger, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl

Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time Feng Zhu, Andrew Sedler, Harrison A Grier, Nauman Ahad, Mark Davenport, Matthew Kaufman, Andrea Giovannucci, Chethan Pandarinath

Solving Min-Max Optimization with Hidden Structure via Gradient Descent Ascent Emmanouil-Vasileios Vlatakis-Gkaragkounis, Lampros Flokas, Georgios Piliouras

Luna: Linear Unified Nested Attention Xuezhe Ma, Xiang Kong, Sinong Wang, Chunting Zhou, Jonathan May, Hao Ma, Luke Zettlemoyer

A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics Kai Xu, Akash Srivastava, Dan Gutfreund, Felix Sosa, Tomer Ullman, Josh Tenenbaum, Charles A. Sutton

Zero Time Waste: Recycling Predictions in Early Exit Neural Networks Maciej Wołczyk, Bartosz Wójcik, Klaudia Bałazy, Igor T Podolak, Jacek Tabor, Marek Śmieja, Tomasz Trzcinski

On Model Calibration for Long-Tailed Object Detection and Instance Segmentation Tai-Yu Pan, Cheng Zhang, Yandong Li, Hexiang Hu, Dong Xuan, Soravit Changpinyo, Boqing Gong, Wei-Lun Chao

ReSSL: Relational Self-Supervised Learning with Weak Augmentation Mingkai Zheng, Shan You, Fei Wang, Chen Qian, Changshui Zhang, Xiaogang Wang, Chang Xu

Learning to See by Looking at Noise Manel Baradad Jurjo, Jonas Wulff, Tongzhou Wang, Phillip Isola, Antonio Torralba

Test-Time Personalization with a Transformer for Human Pose Estimation Yizhuo Li, Miao Hao, Zonglin Di, Nitesh Bharadwaj Gundavarapu, Xiaolong Wang

Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN Zhenyu Xie, Zaiyu Huang, Fuwei Zhao, Haoye Dong, Michael Kampffmeyer, Xiaodan Liang

Bias Out-of-the-Box: An Empirical Analysis of Intersectional Occupational Biases in Popular Generative Language Models Hannah Rose Kirk, Yennie Jun, Filippo Volpin, Haider Iqbal, Elias Benussi, Frederic Dreyer, Aleksandar Shtedritski, Yuki Asano

Weisfeiler and Lehman Go Cellular: CW Networks Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yuguang Wang, Pietro Liò, Guido F. Montufar, Michael Bronstein

Cardinality-Regularized Hawkes-Granger Model Tsuyoshi Ide, Georgios Kollias, Dzung Phan, Naoki Abe

Constrained Robust Submodular Partitioning Shengjie Wang, Tianyi Zhou, Chandrashekhar Lavania, Jeff A Bilmes

Online Knapsack with Frequency Predictions Sungjin Im, Ravi Kumar, Mahshid Montazer Qaem, Manish Purohit

On Component Interactions in Two-Stage Recommender Systems Jiri Hron, Karl Krauth, Michael I. Jordan, Niki Kilbertus

Goal-Aware Cross-Entropy for Multi-Target Reinforcement Learning Kibeom Kim, Min Whoo Lee, Yoonsung Kim, JeHwan Ryu, Minsu Lee, Byoung-Tak Zhang

Smooth Normalizing Flows Jonas Köhler, Andreas Krämer, Frank Noe

Accumulative Poisoning Attacks on Real-time Data Tianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su, Jun Zhu

Estimating the Long-Term Effects of Novel Treatments Keith Battocchi, Eleanor Dillon, Maggie Hei, Greg Lewis, Miruna Oprescu, Vasilis Syrgkanis

Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning Jongjin Park, Younggyo Seo, Chang Liu, Li Zhao, Tao Qin, Jinwoo Shin, Tie-Yan Liu

Multiclass Boosting and the Cost of Weak Learning Nataly Brukhim, Elad Hazan, Shay Moran, Indraneel Mukherjee, Robert E. Schapire

Hyperparameter Optimization Is Deceiving Us, and How to Stop It A. Feder Cooper, Yucheng Lu, Jessica Forde, Christopher M De Sa

Framing RNN as a kernel method: A neural ODE approach Adeline Fermanian, Pierre Marion, Jean-Philippe Vert, Gérard Biau

AutoBalance: Optimized Loss Functions for Imbalanced Data Mingchen Li, Xuechen Zhang, Christos Thrampoulidis, Jiasi Chen, Samet Oymak

SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes Zhaozhi Qian, Yao Zhang, Ioana Bica, Angela Wood, Mihaela van der Schaar

Statistical Query Lower Bounds for List-Decodable Linear Regression Ilias Diakonikolas, Daniel Kane, Ankit Pensia, Thanasis Pittas, Alistair Stewart

Exploring Forensic Dental Identification with Deep Learning Yuan Liang, Weikun Han, Liang Qiu, Chen Wu, Yiting Shao, Kun Wang, Lei He

Dangers of Bayesian Model Averaging under Covariate Shift Pavel Izmailov, Patrick Nicholson, Sanae Lotfi, Andrew G Wilson

Learning Equilibria in Matching Markets from Bandit Feedback Meena Jagadeesan, Alexander Wei, Yixin Wang, Michael I. Jordan, Jacob Steinhardt

Towards Lower Bounds on the Depth of ReLU Neural Networks Christoph Hertrich, Amitabh Basu, Marco Di Summa, Martin Skutella

Pooling by Sliced-Wasserstein Embedding Navid Naderializadeh, Joseph F Comer, Reed Andrews, Heiko Hoffmann, Soheil Kolouri

On the Theory of Reinforcement Learning with Once-per-Episode Feedback Niladri Chatterji, Aldo Pacchiano, Peter L. Bartlett, Michael I. Jordan

Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization Kartik Ahuja, Ethan Caballero, Dinghuai Zhang, Jean-Christophe Gagnon-Audet, Yoshua Bengio, Ioannis Mitliagkas, Irina Rish

BayesIMP: Uncertainty Quantification for Causal Data Fusion Siu Lun Chau, Jean-Francois Ton, Javier González, Yee W. Teh, Dino Sejdinovic

Neural Auto-Curricula in Two-Player Zero-Sum Games Xidong Feng, Oliver Slumbers, Ziyu Wan, Bo Liu, Stephen McAleer, Ying Wen, Jun Wang, Yaodong Yang

Adversarial Robustness of Streaming Algorithms through Importance Sampling Vladimir Braverman, Avinatan Hassidim, Yossi Matias, Mariano Schain, Sandeep Silwal, Samson Zhou

Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data Ashraful Islam, Chun-Fu (Richard) Chen, Rameswar Panda, Leonid Karlinsky, Rogerio Feris, Richard J. Radke

Control Variates for Slate Off-Policy Evaluation Nikos Vlassis, Ashok Chandrashekar, Fernando Amat, Nathan Kallus

On Effective Scheduling of Model-based Reinforcement Learning Hang Lai, Jian Shen, Weinan Zhang, Yimin Huang, Xing Zhang, Ruiming Tang, Yong Yu, Zhenguo Li

Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience Dominic Gonschorek, Larissa Höfling, Klaudia P. Szatko, Katrin Franke, Timm Schubert, Benjamin Dunn, Philipp Berens, David Klindt, Thomas Euler

Episodic Multi-agent Reinforcement Learning with Curiosity-driven Exploration Lulu Zheng, Jiarui Chen, Jianhao Wang, Jiamin He, Yujing Hu, Yingfeng Chen, Changjie Fan, Yang Gao, Chongjie Zhang

Towards a Unified Game-Theoretic View of Adversarial Perturbations and Robustness Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Yiting Chen, Xu Cheng, Xin Wang, Meng Zhou, Jie Shi, Quanshi Zhang

Information Directed Reward Learning for Reinforcement Learning David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause

SSMF: Shifting Seasonal Matrix Factorization Koki Kawabata, Siddharth Bhatia, Rui Liu, Mohit Wadhwa, Bryan Hooi

Associative Memories via Predictive Coding Tommaso Salvatori, Yuhang Song, Yujian Hong, Lei Sha, Simon Frieder, Zhenghua Xu, Rafal Bogacz, Thomas Lukasiewicz

Robust and differentially private mean estimation Xiyang Liu, Weihao Kong, Sham Kakade, Sewoong Oh

Deep Self-Dissimilarities as Powerful Visual Fingerprints Idan Kligvasser, Tamar Shaham, Yuval Bahat, Tomer Michaeli

Celebrating Diversity in Shared Multi-Agent Reinforcement Learning Chenghao Li, Tonghan Wang, Chengjie Wu, Qianchuan Zhao, Jun Yang, Chongjie Zhang

Rebounding Bandits for Modeling Satiation Effects Liu Leqi, Fatma Kilinc Karzan, Zachary Lipton, Alan Montgomery

Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond Maria-Florina F Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik

IQ-Learn: Inverse soft-Q Learning for Imitation Divyansh Garg, Shuvam Chakraborty, Chris Cundy, Jiaming Song, Stefano Ermon

Speedy Performance Estimation for Neural Architecture Search Robin Ru, Clare Lyle, Lisa Schut, Miroslav Fil, Mark van der Wilk, Yarin Gal

How Tight Can PAC-Bayes be in the Small Data Regime? Andrew Foong, Wessel Bruinsma, David Burt, Richard Turner

Environment Generation for Zero-Shot Compositional Reinforcement Learning Izzeddin Gur, Natasha Jaques, Yingjie Miao, Jongwook Choi, Manoj Tiwari, Honglak Lee, Aleksandra Faust

Optimizing Conditional Value-At-Risk of Black-Box Functions Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet

E(n) Equivariant Normalizing Flows Victor Garcia Satorras, Emiel Hoogeboom, Fabian Fuchs, Ingmar Posner, Max Welling

Improving Robustness using Generated Data Sven Gowal, Sylvestre-Alvise Rebuffi, Olivia Wiles, Florian Stimberg, Dan Andrei Calian, Timothy A Mann

Learning to Learn Graph Topologies Xingyue Pu, Tianyue Cao, Xiaoyun Zhang, Xiaowen Dong, Siheng Chen

Pruning Randomly Initialized Neural Networks with Iterative Randomization Daiki Chijiwa, Shin'ya Yamaguchi, Yasutoshi Ida, Kenji Umakoshi, Tomohiro INOUE

Regime Switching Bandits Xiang Zhou, Yi Xiong, Ningyuan Chen, Xuefeng GAO

Aligning Silhouette Topology for Self-Adaptive 3D Human Pose Recovery Ramesha Rakesh Mugaludi, Jogendra Nath Kundu, Varun Jampani, Venkatesh Babu R

Flexible Option Learning Martin Klissarov, Doina Precup

Online Facility Location with Multiple Advice Matteo Almanza, Flavio Chierichetti, Silvio Lattanzi, Alessandro Panconesi, Giuseppe Re

Credit Assignment in Neural Networks through Deep Feedback Control Alexander Meulemans, Matilde Tristany Farinha, Javier Garcia Ordonez, Pau Vilimelis Aceituno, João Sacramento, Benjamin F. Grewe

Robust Online Correlation Clustering Silvio Lattanzi, Benjamin Moseley, Sergei Vassilvitskii, Yuyan Wang, Rudy Zhou

Neural Additive Models: Interpretable Machine Learning with Neural Nets Rishabh Agarwal, Levi Melnick, Nicholas Frosst, Xuezhou Zhang, Ben Lengerich, Rich Caruana, Geoffrey E. Hinton

Generalized Shape Metrics on Neural Representations Alex H Williams, Erin Kunz, Simon Kornblith, Scott Linderman

Diverse Message Passing for Attribute with Heterophily Liang Yang, Mengzhe Li, Liyang Liu, bingxin niu, Chuan Wang, Xiaochun Cao, Yuanfang Guo

Towards Robust Bisimulation Metric Learning Mete Kemertas, Tristan Aumentado-Armstrong

Volume Rendering of Neural Implicit Surfaces Lior Yariv, Jiatao Gu, Yoni Kasten, Yaron Lipman

MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Sean Welleck, Yejin Choi, Zaid Harchaoui

Accurately Solving Rod Dynamics with Graph Learning Han Shao, Tassilo Kugelstadt, Torsten Hädrich, Wojtek Palubicki, Jan Bender, Soeren Pirk, Dominik L Michels

Overcoming the Convex Barrier for Simplex Inputs Harkirat Singh Behl, M. Pawan Kumar, Philip Torr, Krishnamurthy Dvijotham

Coupled Segmentation and Edge Learning via Dynamic Graph Propagation Zhiding Yu, Rui Huang, Wonmin Byeon, Sifei Liu, Guilin Liu, Thomas Breuel, Anima Anandkumar, Jan Kautz

Offline RL Without Off-Policy Evaluation David Brandfonbrener, Will Whitney, Rajesh Ranganath, Joan Bruna

CrypTen: Secure Multi-Party Computation Meets Machine Learning Brian Knott, Shobha Venkataraman, Awni Hannun, Shubho Sengupta, Mark Ibrahim, Laurens van der Maaten

Can contrastive learning avoid shortcut solutions? Joshua W. Robinson, Li Sun, Ke Yu, Kayhan Batmanghelich, Stefanie Jegelka, Suvrit Sra

Convex Polytope Trees Mohammadreza Armandpour, Ali Sadeghian, Mingyuan Zhou

SketchGen: Generating Constrained CAD Sketches Wamiq Para, Shariq Bhat, Paul Guerrero, Tom Kelly, Niloy Mitra, Leonidas Guibas, Peter Wonka

Differentially Private n-gram Extraction Kunho Kim, Sivakanth Gopi, Janardhan Kulkarni, Sergey Yekhanin

Noisy Recurrent Neural Networks Soon Hoe Lim, N. Benjamin Erichson, Liam Hodgkinson, Michael W. Mahoney

Matrix encoding networks for neural combinatorial optimization Yeong-Dae Kwon, Jinho Choo, Iljoo Yoon, Minah Park, Duwon Park, Youngjune Gwon

Continuous Latent Process Flows Ruizhi Deng, Marcus A Brubaker, Greg Mori, Andreas Lehrmann

SPANN: Highly-efficient Billion-scale Approximate Nearest Neighborhood Search Qi Chen, Bing Zhao, Haidong Wang, Mingqin Li, Chuanjie Liu, Zengzhong Li, Mao Yang, Jingdong Wang

Distilling Object Detectors with Feature Richness Du Zhixing, Rui Zhang, Ming Chang, xishan zhang, Shaoli Liu, Tianshi Chen, Yunji Chen

Grounding Spatio-Temporal Language with Transformers Tristan Karch, Laetitia Teodorescu, Katja Hofmann, Clément Moulin-Frier, Pierre-Yves Oudeyer

Learning where to learn: Gradient sparsity in meta and continual learning Johannes von Oswald, Dominic Zhao, Seijin Kobayashi, Simon Schug, Massimo Caccia, Nicolas Zucchet, João Sacramento

Efficient Equivariant Network Lingshen He, Yuxuan Chen, zhengyang shen, Yiming Dong, Yisen Wang, Zhouchen Lin

Imitation with Neural Density Models Kuno Kim, Akshat Jindal, Yang Song, Jiaming Song, Yanan Sui, Stefano Ermon

Accurate Point Cloud Registration with Robust Optimal Transport Zhengyang Shen, Jean Feydy, Peirong Liu, Ariel H Curiale, Ruben San Jose Estepar, Raul San Jose Estepar, Marc Niethammer

Automatic Data Augmentation for Generalization in Reinforcement Learning Roberta Raileanu, Maxwell Goldstein, Denis Yarats, Ilya Kostrikov, Rob Fergus

Blending Anti-Aliasing into Vision Transformer Shengju Qian, Hao Shao, Yi Zhu, Mu Li, Jiaya Jia

The Benefits of Implicit Regularization from SGD in Least Squares Problems Difan Zou, Jingfeng Wu, Vladimir Braverman, Quanquan Gu, Dean P. Foster, Sham Kakade

MarioNette: Self-Supervised Sprite Learning Dmitriy Smirnov, MICHAEL GHARBI, Matthew Fisher, Vitor Guizilini, Alexei Efros, Justin M Solomon

RLlib Flow: Distributed Reinforcement Learning is a Dataflow Problem Eric Liang, Zhanghao Wu, Michael Luo, Sven Mika, Joseph E Gonzalez, Ion Stoica

Parameter Inference with Bifurcation Diagrams Gregory Szep, Neil Dalchau, Attila Csikász-Nagy

Scalable Thompson Sampling using Sparse Gaussian Process Models Sattar Vakili, Henry Moss, Artem Artemev, Vincent Dutordoir, Victor Picheny

Robust Counterfactual Explanations on Graph Neural Networks Mohit Bajaj, Lingyang Chu, Zi Yu Xue, Jian Pei, Lanjun Wang, Peter Cho-Ho Lam, Yong Zhang

Similarity and Matching of Neural Network Representations Adrián Csiszárik, Péter Kőrösi-Szabó, Ákos Matszangosz, Gergely Papp, Dániel Varga

DOCTOR: A Simple Method for Detecting Misclassification Errors Federica Granese, Marco Romanelli, Daniele Gorla, Catuscia Palamidessi, Pablo Piantanida

Contrastive Laplacian Eigenmaps Hao Zhu, Ke Sun, Peter Koniusz

Shape Registration in the Time of Transformers Giovanni Trappolini, Luca Cosmo, Luca Moschella, Riccardo Marin, Simone Melzi, Emanuele Rodolà

Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning Hyunsoo Chung, Jungtaek Kim, Boris Knyazev, Jinhwi Lee, Graham W. Taylor, Jaesik Park, Minsu Cho

Dynamic Grained Encoder for Vision Transformers Lin Song, Songyang Zhang, Songtao Liu, Zeming Li, Xuming He, Hongbin Sun, Jian Sun, Nanning Zheng

On UMAP's True Loss Function Sebastian Damrich, Fred A. Hamprecht

Fast Pure Exploration via Frank-Wolfe Po-An Wang, Ruo-Chun Tzeng, Alexandre Proutiere

Computer-Aided Design as Language Yaroslav Ganin, Sergey Bartunov, Yujia Li, Ethan Keller, Stefano Saliceti

ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE Qingzhong Ai, LIRONG HE, SHIYU LIU, Zenglin Xu

Group Equivariant Subsampling Jin Xu, Hyunjik Kim, Thomas Rainforth, Yee W. Teh

Data Sharing and Compression for Cooperative Networked Control Jiangnan Cheng, Marco Pavone, Sachin Katti, Sandeep Chinchali, Ao Tang

Searching for Efficient Transformers for Language Modeling David So, Wojciech Mańke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V Le

Bubblewrap: Online tiling and real-time flow prediction on neural manifolds Anne Draelos, Pranjal Gupta, Na Young Jun, Chaichontat Sriworarat, John C. Pearson

Learning Causal Semantic Representation for Out-of-Distribution Prediction Chang Liu, Xinwei Sun, Jindong Wang, Haoyue Tang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu

Adversarial Robustness with Semi-Infinite Constrained Learning Alexander Robey, Luiz Chamon, George J. Pappas, Hamed Hassani, Alejandro Ribeiro

Conformal Time-series Forecasting Kamile Stankeviciute, Ahmed M. Alaa, Mihaela van der Schaar

Bootstrapping the Error of Oja's Algorithm Robert Lunde, Purnamrita Sarkar, Rachel Ward

Curriculum Offline Imitating Learning Minghuan Liu, Hanye Zhao, Zhengyu Yang, Jian Shen, Weinan Zhang, Li Zhao, Tie-Yan Liu

Collaborative Uncertainty in Multi-Agent Trajectory Forecasting Bohan Tang, Yiqi Zhong, Ulrich Neumann, Gang Wang, Siheng Chen, Ya Zhang

Probabilistic Forecasting: A Level-Set Approach Hilaf Hasson, Bernie Wang, Tim Januschowski, Jan Gasthaus

A/B Testing for Recommender Systems in a Two-sided Marketplace Preetam Nandy, Divya Venugopalan, Chun Lo, Shaunak Chatterjee

Retiring Adult: New Datasets for Fair Machine Learning Frances Ding, Moritz Hardt, John P. Miller, Ludwig Schmidt

Neural Pseudo-Label Optimism for the Bank Loan Problem Aldo Pacchiano, Shaun Singh, Edward Chou, Alex Berg, Jakob Foerster

Learning 3D Dense Correspondence via Canonical Point Autoencoder An-Chieh Cheng, Xueting Li, Min Sun, Ming-Hsuan Yang, Sifei Liu

Speech-T: Transducer for Text to Speech and Beyond Jiawei Chen, Xu Tan, Yichong Leng, Jin Xu, Guihua Wen, Tao Qin, Tie-Yan Liu

Bellman-consistent Pessimism for Offline Reinforcement Learning Tengyang Xie, Ching-An Cheng, Nan Jiang, Paul Mineiro, Alekh Agarwal

Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Furong Huang, Uzi Vishkin, Micah Goldblum, Tom Goldstein

Sub-Linear Memory: How to Make Performers SLiM Valerii Likhosherstov, Krzysztof M Choromanski, Jared Quincy Davis, Xingyou Song, Adrian Weller

VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization Mucong Ding, Kezhi Kong, Jingling Li, Chen Zhu, John Dickerson, Furong Huang, Tom Goldstein

Asynchronous Decentralized SGD with Quantized and Local Updates Giorgi Nadiradze, Amirmojtaba Sabour, Peter Davies, Shigang Li, Dan Alistarh

Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret Jean Tarbouriech, Runlong Zhou, Simon S Du, Matteo Pirotta, Michal Valko, Alessandro Lazaric

Sim and Real: Better Together Shirli Di-Castro, Dotan Di Castro, Shie Mannor

Does Knowledge Distillation Really Work? Samuel Stanton, Pavel Izmailov, Polina Kirichenko, Alexander A Alemi, Andrew G Wilson

Teachable Reinforcement Learning via Advice Distillation Olivia Watkins, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, Jacob Andreas

Antipodes of Label Differential Privacy: PATE and ALIBI Mani Malek Esmaeili, Ilya Mironov, Karthik Prasad, Igor Shilov, Florian Tramer

Visual Search Asymmetry: Deep Nets and Humans Share Similar Inherent Biases Shashi Kant Gupta, Mengmi Zhang, CHIA-CHIEN WU, Jeremy Wolfe, Gabriel Kreiman

Adversarial Attacks on Graph Classifiers via Bayesian Optimisation Xingchen Wan, Henry Kenlay, Robin Ru, Arno Blaas, Michael A Osborne, Xiaowen Dong

argmax centroid Chengyue Gong, Mao Ye, Qiang Liu

HRFormer: High-Resolution Vision Transformer for Dense Predict YUHUI YUAN, Rao Fu, Lang Huang, Weihong Lin, Chao Zhang, Xilin Chen, Jingdong Wang

Manifold Topology Divergence: a Framework for Comparing Data Manifolds. Serguei Barannikov, Ilya Trofimov, Grigorii Sotnikov, Ekaterina Trimbach, Alexander Korotin, Alexander Filippov, Evgeny Burnaev

Meta-learning with an Adaptive Task Scheduler Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn

Neural Active Learning with Performance Guarantees Zhilei Wang, Pranjal Awasthi, Christoph Dann, Ayush Sekhari, Claudio Gentile

Edge Representation Learning with Hypergraphs Jaehyeong Jo, Jinheon Baek, Seul Lee, Dongki Kim, Minki Kang, Sung Ju Hwang

LEADS: Learning Dynamical Systems that Generalize Across Environments Yuan Yin, Ibrahim Ayed, Emmanuel de Bézenac, Nicolas Baskiotis, Patrick Gallinari

Robustness of Graph Neural Networks at Scale Simon Geisler, Tobias Schmidt, Hakan Şirin, Daniel Zügner, Aleksandar Bojchevski, Stephan Günnemann

Cortico-cerebellar networks as decoupling neural interfaces Joseph Pemberton, Ellen Boven, Richard Apps, Rui Ponte Costa

Challenges and Opportunities in High Dimensional Variational Inference Akash Kumar Dhaka, Alejandro Catalina, Manushi Welandawe, Michael R Andersen, Jonathan Huggins, Aki Vehtari

On the Expressivity of Markov Reward David Abel, Will Dabney, Anna Harutyunyan, Mark K Ho, Michael L. Littman, Doina Precup, Satinder P. Singh

Neural Scene Flow Prior Xueqian Li, Jhony Kaesemodel Pontes, Simon Lucey

Grammar-Based Grounded Lexicon Learning Jiayuan Mao, Freda Shi, Jiajun Wu, Roger P. Levy, Josh Tenenbaum

Neural Ensemble Search for Uncertainty Estimation and Dataset Shift Sheheryar Zaidi, Arber Zela, Thomas Elsken, Chris C Holmes, Frank Hutter, Yee W. Teh

Learning to Elect Cem Anil, Xuchan Bao

Rethinking gradient sparsification as total error minimization Atal Sahu, Aritra Dutta, Ahmed M. Abdelmoniem, Trambak Banerjee, Marco Canini, Panos Kalnis

Approximate optimization of convex functions with outlier noise Anindya De, Sanjeev Khanna, Huan Li, MohammadHesam NikpeySalekde

Distributed Saddle-Point Problems Under Data Similarity Aleksandr Beznosikov, Gesualdo Scutari, Alexander Rogozin, Alexander Gasnikov

K-level Reasoning for Zero-Shot Coordination in Hanabi Brandon Cui, Hengyuan Hu, Luis Pineda, Jakob Foerster

Functionally Regionalized Knowledge Transfer for Low-resource Drug Discovery Huaxiu Yao, Ying Wei, Long-Kai Huang, Ding Xue, Junzhou Huang, Zhenhui (Jessie) Li

Measuring Generalization with Optimal Transport Ching-Yao Chuang, Youssef Mroueh, Kristjan Greenewald, Antonio Torralba, Stefanie Jegelka

Learning Signal-Agnostic Manifolds of Neural Fields Yilun Du, Katie Collins, Josh Tenenbaum, Vincent Sitzmann

Diversity Matters When Learning From Ensembles Giung Nam, Jongmin Yoon, Yoonho Lee, Juho Lee

Personalized Federated Learning With Gaussian Processes Idan Achituve, Aviv Shamsian, Aviv Navon, Gal Chechik, Ethan Fetaya

Implicit SVD for Graph Representation Learning Sami Abu-El-Haija, Hesham Mostafa, Marcel Nassar, Valentino Crespi, Greg Ver Steeg, Aram Galstyan

Offline Model-based Adaptable Policy Learning Xiong-Hui Chen, Yang Yu, Qingyang Li, Fan-Ming Luo, Zhiwei Qin, Wenjie Shang, Jieping Ye

Active clustering for labeling training data Quentin Lutz, Elie de Panafieu, Maya Stein, Alex Scott

Ensembling Graph Predictions for AMR Parsing Thanh Lam Hoang, Gabriele Picco, Yufang Hou, Young-Suk Lee, Lam Nguyen, Dzung Phan, Vanessa Lopez, Ramon Fernandez Astudillo

Mixture Proportion Estimation and PU Learning:A Modern Approach Saurabh Garg, Yifan Wu, Alexander J Smola, Sivaraman Balakrishnan, Zachary Lipton

Scaling Vision with Sparse Mixture of Experts Carlos Riquelme, Joan Puigcerver, Basil Mustafa, Maxim Neumann, Rodolphe Jenatton, André Susano Pinto, Daniel Keysers, Neil Houlsby

Two-sided fairness in rankings via Lorenz dominance Virginie Do, Sam Corbett-Davies, Jamal Atif, Nicolas Usunier

Machine Learning for Variance Reduction in Online Experiments Yongyi Guo, Dominic Coey, Mikael Konutgan, Wenting Li, Chris Schoener, Matt Goldman

Multi-Facet Clustering Variational Autoencoders Fabian Falck, Haoting Zhang, Matthew Willetts, George Nicholson, Christopher Yau, Chris C Holmes

Synthetic Design: An Optimization Approach to Experimental Design with Synthetic Controls Nick Doudchenko, Khashayar Khosravi, Jean Pouget-Abadie, Sébastien Lahaie, Miles Lubin, Vahab Mirrokni, Jann Spiess, guido imbens

Ranking Policy Decisions Hadrien Pouget, Hana Chockler, Youcheng Sun, Daniel Kroening

Searching the Search Space of Vision Transformer Minghao Chen, Kan Wu, Bolin Ni, Houwen Peng, Bei Liu, Jianlong Fu, Hongyang Chao, Haibin Ling

Inverse Problems Leveraging Pre-trained Contrastive Representations Sriram Ravula, Georgios Smyrnis, Matt Jordan, Alexandros G Dimakis

SAPE: Spatially-Adaptive Progressive Encoding for Neural Optimization Amir Hertz, Or Perel, Raja Giryes, Olga Sorkine-hornung, Daniel Cohen-or

Cooperative Stochastic Bandits with Asynchronous Agents and Constrained Feedback Lin Yang, Yu-Zhen Janice Chen, Stephen Pasteris, Mohammad Hajiesmaili, John C. S. Lui, Don Towsley

Gone Fishing: Neural Active Learning with Fisher Embeddings Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Sham Kakade

Refining Language Models with Compositional Explanations Huihan Yao, Ying Chen, Qinyuan Ye, Xisen Jin, Xiang Ren

Going Beyond Linear RL: Sample Efficient Neural Function Approximation Baihe Huang, Kaixuan Huang, Sham Kakade, Jason Lee, Qi Lei, Runzhe Wang, Jiaqi Yang

What can linearized neural networks actually say about generalization? Guillermo Ortiz-Jimenez, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard

CATs: Cost Aggregation Transformers for Visual Correspondence Seokju Cho, Sunghwan Hong, Sangryul Jeon, Yunsung Lee, Kwanghoon Sohn, Seungryong Kim

Asynchronous Stochastic Optimization Robust to Arbitrary Delays Alon Cohen, Amit Daniely, Yoel Drori, Tomer Koren, Mariano Schain

Denoising Normalizing Flow Christian Horvat, Jean-Pascal Pfister

Differentiable Learning Under Triage Nastaran Okati, Abir De, Manuel Rodriguez

ROI Maximization in Stochastic Online Decision-Making Nicolò Cesa-Bianchi, Tom Cesari, Yishay Mansour, Vianney Perchet

Pay Attention to MLPs Hanxiao Liu, Zihang Dai, David So, Quoc V Le

Adversarial Examples in Multi-Layer Random ReLU Networks Peter L. Bartlett, Sebastien Bubeck, Yeshwanth Cherapanamjeri

Realistic evaluation of transductive few-shot learning Olivier Veilleux, Malik Boudiaf, Pablo Piantanida, Ismail Ben Ayed

Twins: Revisiting the Design of Spatial Attention in Vision Transformers Xiangxiang Chu, Zhi Tian, Yuqing Wang, Bo Zhang, Haibing Ren, Xiaolin Wei, Huaxia Xia, Chunhua Shen

Learning Graph Models for Retrosynthesis Prediction Vignesh Ram Somnath, Charlotte Bunne, Connor Coley, Andreas Krause, Regina Barzilay

Deep Neural Networks as Point Estimates for Deep Gaussian Processes Vincent Dutordoir, James Hensman, Mark van der Wilk, Carl Henrik Ek, Zoubin Ghahramani, Nicolas Durrande

Private and Non-private Uniformity Testing for Ranking Data Róbert Busa-Fekete, Dimitris Fotakis, Emmanouil Zampetakis

Model-Based Reinforcement Learning via Imagination with Derived Memory Yao Mu, Yuzheng Zhuang, Bin Wang, Guangxiang Zhu, Wulong Liu, Jianyu Chen, Ping Luo, Shengbo Li, Chongjie Zhang, Jianye Hao

Causal Abstractions of Neural Networks Atticus Geiger, Hanson Lu, Thomas Icard, Christopher Potts

3DP3: 3D Scene Perception via Probabilistic Programming Nishad Gothoskar, Marco Cusumano-Towner, Ben Zinberg, Matin Ghavamizadeh, Falk Pollok, Austin Garrett, Josh Tenenbaum, Dan Gutfreund, Vikash K. Mansinghka

MADE: Exploration via Maximizing Deviation from Explored Regions Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph E Gonzalez, Stuart J. Russell

Variational Automatic Curriculum Learning for Sparse-Reward Cooperative Multi-Agent Problems Jiayu Chen, Yuanxin Zhang, Yuanfan Xu, Huimin Ma, Huazhong Yang, Jiaming Song, Yu Wang, Yi Wu

Align before Fuse: Vision and Language Representation Learning with Momentum Distillation Junnan Li, Ramprasaath Selvaraju, Akhilesh Gotmare, Shafiq Joty, Caiming Xiong, Steven Chu Hong Hoi

Variational Model Inversion Attacks Kuan-Chieh Wang, YAN FU, Ke Li, Ashish Khisti, Richard S. Zemel, Alireza Makhzani

Graph Neural Networks with Adaptive Residual Xiaorui Liu, Jiayuan Ding, Wei Jin, Han Xu, Yao Ma, Zitao Liu, Jiliang Tang

Calibration and Consistency of Adversarial Surrogate Losses Pranjal Awasthi, Natalie Frank, Anqi Mao, Mehryar Mohri, Yutao Zhong

Robust Implicit Networks via Non-Euclidean Contractions Saber Jafarpour, Alexander Davydov, Anton Proskurnikov, Francesco Bullo

Sparse Training via Boosting Pruning Plasticity with Neuroregeneration Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu

Low-Fidelity Video Encoder Optimization for Temporal Action Localization Mengmeng Xu, Juan Manuel Perez Rua, Xiatian Zhu, Bernard Ghanem, Brais Martinez

Practical Near Neighbor Search via Group Testing Joshua Engels, Benjamin Coleman, Anshumali Shrivastava

Neural Hybrid Automata: Learning Dynamics With Multiple Modes and Stochastic Transitions Michael Poli, Stefano Massaroli, Luca Scimeca, Sanghyuk Chun, Seong Joon Oh, Atsushi Yamashita, Hajime Asama, Jinkyoo Park, Animesh Garg

Meta-Adaptive Nonlinear Control: Theory and Algorithms Guanya Shi, Kamyar Azizzadenesheli, Michael O'Connell, Soon-Jo Chung, Yisong Yue

Compositional Reinforcement Learning from Logical Specifications Kishor Jothimurugan, Suguman Bansal, Osbert Bastani, Rajeev Alur

Differentiable Quality Diversity Matthew Fontaine, Stefanos Nikolaidis

Parameterized Knowledge Transfer for Personalized Federated Learning Jie Zhang, Song Guo, Xiaosong Ma, Haozhao Wang, Wenchao Xu, Feijie Wu

Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions Bruno Loureiro, Gabriele Sicuro, Cedric Gerbelot, Alessandro Pacco, Florent Krzakala, Lenka Zdeborová

Infinite Time Horizon Safety of Bayesian Neural Networks Mathias Lechner, Đorđe Žikelić, Krishnendu Chatterjee, Thomas Henzinger

List-Decodable Mean Estimation in Nearly-PCA Time Ilias Diakonikolas, Daniel Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian

Latent Matters: Learning Deep State-Space Models Alexej Klushyn, Richard Kurle, Maximilian Soelch, Botond Cseke, Patrick van der Smagt

On the Estimation Bias in Double Q-Learning Zhizhou Ren, Guangxiang Zhu, Hao Hu, Beining Han, Jianglun Chen, Chongjie Zhang

Non-Gaussian Gaussian Processes for Few-Shot Regression Marcin Sendera, Jacek Tabor, Aleksandra Nowak, Andrzej Bedychaj, Massimiliano Patacchiola, Tomasz Trzcinski, Przemysław Spurek, Maciej Zieba

Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning Yiqin Yang, Xiaoteng Ma, Chenghao Li, Zewu Zheng, Qiyuan Zhang, Gao Huang, Jun Yang, Qianchuan Zhao

Online Learning in Periodic Zero-Sum Games Tanner Fiez, Ryann Sim, Stratis Skoulakis, Georgios Piliouras, Lillian Ratliff

K-Net: Towards Unified Image Segmentation Wenwei Zhang, Jiangmiao Pang, Kai Chen, Chen Change Loy

Dynaboard: An Evaluation-As-A-Service Platform for Holistic Next-Generation Benchmarking Zhiyi Ma, Kawin Ethayarajh, Tristan Thrush, Somya Jain, Ledell Wu, Robin Jia, Christopher Potts, Adina Williams, Douwe Kiela

Faster Matchings via Learned Duals Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii

Modality-Agnostic Topology Aware Localization Farhad Ghazvinian Zanjani, Ilia Karmanov, Hanno Ackermann, Daniel Dijkman, Simone Merlin, Max Welling, Fatih Porikli

Kernel Identification Through Transformers Fergus Simpson, Ian Davies, Vidhi Lalchand, Alessandro Vullo, Nicolas Durrande, Carl Edward Rasmussen

Parallelizing Thompson Sampling Amin Karbasi, Vahab Mirrokni, Mohammad Shadravan

Dynamic Causal Bayesian Optimization Virginia Aglietti, Neil Dhir, Javier González, Theodoros Damoulas

Emergent Discrete Communication in Semantic Spaces Mycal Tucker, Huao Li, Siddharth Agrawal, Dana Hughes, Katia Sycara, Michael Lewis, Julie A Shah

Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity Ran Liu, Mehdi Azabou, Max Dabagia, Chi-Heng Lin, Mohammad Gheshlaghi Azar, Keith Hengen, Michal Valko, Eva Dyer

Universal Graph Convolutional Networks Di Jin, Zhizhi Yu, Cuiying Huo, Rui Wang, Xiao Wang, Dongxiao He, Jiawei Han

Neural-PIL: Neural Pre-Integrated Lighting for Reflectance Decomposition Mark Boss, Varun Jampani, Raphael Braun, Ce Liu, Jonathan Barron, Hendrik PA Lensch

Information is Power: Intrinsic Control via Information Capture Nicholas Rhinehart, Jenny Wang, Glen Berseth, John Co-Reyes, Danijar Hafner, Chelsea Finn, Sergey Levine

Extracting Deformation-Aware Local Features by Learning to Deform Guilherme Potje, Renato Martins, Felipe Chamone, Erickson Nascimento

Stochastic Bias-Reduced Gradient Methods Hilal Asi, Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford

A Separation Result Between Data-oblivious and Data-aware Poisoning Attacks Samuel Deng, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Abhradeep Guha Thakurta

R-Drop: Regularized Dropout for Neural Networks xiaobo liang, Lijun Wu, Juntao Li, Yue Wang, Qi Meng, Tao Qin, Wei Chen, Min Zhang, Tie-Yan Liu

What Makes Multi-Modal Learning Better than Single (Provably) Yu Huang, Chenzhuang Du, Zihui Xue, Xuanyao Chen, Hang Zhao, Longbo Huang

Dynamic Inference with Neural Interpreters Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi, Peter V. Gehler, Yoshua Bengio, Francesco Locatello, Bernhard Schölkopf

Selective Sampling for Online Best-arm Identification Romain Camilleri, Zhihan Xiong, Maryam Fazel, Lalit Jain, Kevin G. Jamieson

Multi-task Learning of Order-Consistent Causal Graphs Xinshi Chen, Haoran Sun, Caleb Ellington, Eric P. Xing, Le Song

Learning interaction rules from multi-animal trajectories via augmented behavioral models Keisuke Fujii, Naoya Takeishi, Kazushi Tsutsui, Emyo Fujioka, Nozomi Nishiumi, Ryoya Tanaka, Mika Fukushiro, Kaoru Ide, Hiroyoshi Kohno, Ken Yoda, Susumu Takahashi, Shizuko Hiryu, Yoshinobu Kawahara

Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications Leonard Berrada, Sumanth Dathathri, Krishnamurthy Dvijotham, Robert Stanforth, Rudy R Bunel, Jonathan Uesato, Sven Gowal, M. Pawan Kumar

Controlling Neural Networks with Rule Representations Sungyong Seo, Sercan Arik, Jinsung Yoon, Xiang Zhang, Kihyuk Sohn, Tomas Pfister

Federated Reconstruction: Partially Local Federated Learning Karan Singhal, Hakim Sidahmed, Zachary Garrett, Shanshan Wu, John Rush, Sushant Prakash

Subquadratic Overparameterization for Shallow Neural Networks ChaeHwan Song, Ali Ramezani-Kebrya, Thomas Pethick, Armin Eftekhari, Volkan Cevher

Continuous Doubly Constrained Batch Reinforcement Learning Rasool Fakoor, Jonas W Mueller, Kavosh Asadi, Pratik Chaudhari, Alexander J Smola

Deep Conditional Gaussian Mixture Model for Constrained Clustering Laura Manduchi, Kieran Chin-Cheong, Holger Michel, Sven Wellmann, Julia Vogt

Bootstrap Your Object Detector via Mixed Training Mengde Xu, Zheng Zhang, Fangyun Wei, Yutong Lin, Yue Cao, Stephen Lin, Han Hu, Xiang Bai

Online Adaptation to Label Distribution Shift Ruihan Wu, Chuan Guo, Yi Su, Kilian Q. Weinberger

Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression Zhaozhi Qian, William Zame, Lucas Fleuren, Paul Elbers, Mihaela van der Schaar

Entropic Desired Dynamics for Intrinsic Control Steven Hansen, Guillaume Desjardins, Kate Baumli, David Warde-Farley, Nicolas Heess, Simon Osindero, Volodymyr Mnih

Learning to dehaze with polarization Chu Zhou, Minggui Teng, Yufei Han, Chao Xu, Boxin Shi

Conservative Data Sharing for Multi-Task Offline Reinforcement Learning Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Sergey Levine, Chelsea Finn

What’s a good imputation to predict with missing values? Marine Le Morvan, Julie Josse, Erwan Scornet, Gael Varoquaux

Hierarchical Skills for Efficient Exploration Jonas Gehring, Gabriel Synnaeve, Andreas Krause, Nicolas Usunier

Submodular + Concave Siddharth Mitra, Moran Feldman, Amin Karbasi

DeepGEM: Generalized Expectation-Maximization for Blind Inversion Angela Gao, Jorge Castellanos, Yisong Yue, Zachary Ross, Katherine Bouman

Learning to Generate Visual Questions with Noisy Supervision Shen Kai, Lingfei Wu, Siliang Tang, Yueting Zhuang, zhen he, Zhuoye Ding, Yun Xiao, Bo Long

Pure Exploration in Kernel and Neural Bandits Yinglun Zhu, Dongruo Zhou, Ruoxi Jiang, Quanquan Gu, Rebecca Willett, Robert Nowak

Numerical Composition of Differential Privacy Sivakanth Gopi, Yin Tat Lee, Lukas Wutschitz

Sequential Algorithms for Testing Closeness of Distributions Aadil Oufkir, Omar Fawzi, Nicolas Flammarion, Aurélien Garivier

Hyperparameter Tuning is All You Need for LISTA Xiaohan Chen, Jialin Liu, Zhangyang Wang, Wotao Yin

Foundations of Symbolic Languages for Model Interpretability Marcelo Arenas, Daniel Báez, Pablo Barceló, Jorge Pérez, Bernardo Subercaseaux

How Well do Feature Visualizations Support Causal Understanding of CNN Activations? Roland S. Zimmermann, Judy Borowski, Robert Geirhos, Matthias Bethge, Thomas Wallis, Wieland Brendel

Sparse Spiking Gradient Descent Nicolas Perez-Nieves, Dan Goodman

Towards Efficient and Effective Adversarial Training Gaurang Sriramanan, Sravanti Addepalli, Arya Baburaj, Venkatesh Babu R

An Uncertainty Principle is a Price of Privacy-Preserving Microdata John Abowd, Robert Ashmead, Ryan Cumings-Menon, Simson Garfinkel, Daniel Kifer, Philip Leclerc, William Sexton, Ashley Simpson, Christine Task, Pavel Zhuravlev

Fairness in Ranking under Uncertainty Ashudeep Singh, David Kempe, Thorsten Joachims

Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data Gongfan Fang, Yifan Bao, Jie Song, Xinchao Wang, Donglin Xie, Chengchao Shen, Mingli Song

Joint Semantic Mining for Weakly Supervised RGB-D Salient Object Detection Jingjing Li, Wei Ji, Qi Bi, Cheng Yan, Miao Zhang, Yongri Piao, Huchuan Lu, Li cheng

ATISS: Autoregressive Transformers for Indoor Scene Synthesis Despoina Paschalidou, Amlan Kar, Maria Shugrina, Karsten Kreis, Andreas Geiger, Sanja Fidler

Fairness via Representation Neutralization Mengnan Du, Subhabrata Mukherjee, Guanchu Wang, Ruixiang Tang, Ahmed Awadallah, Xia Hu

Residual Relaxation for Multi-view Representation Learning Yifei Wang, Zhengyang Geng, Feng Jiang, Chuming Li, Yisen Wang, Jiansheng Yang, Zhouchen Lin

Do Vision Transformers See Like Convolutional Neural Networks? Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang, Alexey Dosovitskiy

Explaining Latent Representations with a Corpus of Examples Jonathan Crabbe, Zhaozhi Qian, Fergus Imrie, Mihaela van der Schaar

Explaining heterogeneity in medial entorhinal cortex with task-driven neural networks Aran Nayebi, Alexander Attinger, Malcolm Campbell, Kiah Hardcastle, Isabel Low, Caitlin S Mallory, Gabriel Mel, Ben Sorscher, Alex H Williams, Surya Ganguli, Lisa Giocomo, Dan Yamins

FACMAC: Factored Multi-Agent Centralised Policy Gradients Bei Peng, Tabish Rashid, Christian Schroeder de Witt, Pierre-Alexandre Kamienny, Philip Torr, Wendelin Boehmer, Shimon Whiteson

Evaluating Efficient Performance Estimators of Neural Architectures Xuefei Ning, Changcheng Tang, Wenshuo Li, Zixuan Zhou, Shuang Liang, Huazhong Yang, Yu Wang

Differential Privacy Over Riemannian Manifolds Matthew Reimherr, Karthik Bharath, Carlos Soto

How can classical multidimensional scaling go wrong? Rishi Sonthalia, Greg Van Buskirk, Benjamin Raichel, Anna Gilbert

Non-asymptotic Error Bounds for Bidirectional GANs Shiao Liu, Yunfei Yang, Jian Huang, Yuling Jiao, Yang Wang

Causal Navigation by Continuous-time Neural Networks Charles Vorbach, Ramin Hasani, Alexander Amini, Mathias Lechner, Daniela Rus

Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, Max Welling

Keeping Your Eye on the Ball: Trajectory Attention in Video Transformers Mandela Patrick, Dylan Campbell, Yuki Asano, Ishan Misra, Florian Metze, Christoph Feichtenhofer, Andrea Vedaldi, João F. Henriques

Learning with Labeling Induced Abstentions Kareem Amin, Giulia DeSalvo, Afshin Rostamizadeh

Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote Yi-Shan Wu, Andres Masegosa, Stephan Lorenzen, Christian Igel, Yevgeny Seldin

A Multi-Implicit Neural Representation for Fonts Pradyumna Reddy, Zhifei Zhang, Zhaowen Wang, Matthew Fisher, Hailin Jin, Niloy Mitra

OctField: Hierarchical Implicit Functions for 3D Modeling Jia-Heng Tang, Weikai Chen, jie Yang, Bo Wang, Songrun Liu, Bo Yang, Lin Gao

The Inductive Bias of Quantum Kernels Jonas Kübler, Simon Buchholz, Bernhard Schölkopf

Pretraining Representations for Data-Efficient Reinforcement Learning Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R Devon Hjelm, Philip Bachman, Aaron C. Courville

Universal Approximation Using Well-Conditioned Normalizing Flows Holden Lee, Chirag Pabbaraju, Anish Prasad Sevekari, Andrej Risteski

Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? Xiaolong Ma, Geng Yuan, Xuan Shen, Tianlong Chen, Xuxi Chen, Xiaohan Chen, Ning Liu, Minghai Qin, Sijia Liu, Zhangyang Wang, Yanzhi Wang

TokenLearner: Adaptive Space-Time Tokenization for Videos Michael Ryoo, AJ Piergiovanni, Anurag Arnab, Mostafa Dehghani, Anelia Angelova

Tactical Optimism and Pessimism for Deep Reinforcement Learning Ted Moskovitz, Jack Parker-Holder, Aldo Pacchiano, Michael Arbel, Michael I. Jordan

FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout Samuel Horváth, Stefanos Laskaridis, Mario Almeida, Ilias Leontiadis, Stylianos Venieris, Nicholas Lane

Interactive Label Cleaning with Example-based Explanations Stefano Teso, Andrea Bontempelli, Fausto Giunchiglia, Andrea Passerini

Glance-and-Gaze Vision Transformer Qihang Yu, Yingda Xia, Yutong Bai, Yongyi Lu, Alan L. Yuille, Wei Shen

Self-Supervised GANs with Label Augmentation Liang Hou, Huawei Shen, Qi Cao, Xueqi Cheng

Shape As Points: A Differentiable Poisson Solver Songyou Peng, Chiyu Jiang, Yiyi Liao, Michael Niemeyer, Marc Pollefeys, Andreas Geiger

Outcome-Driven Reinforcement Learning via Variational Inference Tim G. J. Rudner, Vitchyr Pong, Rowan McAllister, Yarin Gal, Sergey Levine

Rectifying the Shortcut Learning of Background for Few-Shot Learning Xu Luo, Longhui Wei, Liangjian Wen, Jinrong Yang, Lingxi Xie, Zenglin Xu, Qi Tian

SEAL: Self-supervised Embodied Active Learning using Exploration and 3D Consistency Devendra Singh Chaplot, Murtaza Dalal, Saurabh Gupta, Jitendra Malik, Ruslan Salakhutdinov

Direct Multi-view Multi-person 3D Pose Estimation tao wang, Jianfeng Zhang, Yujun Cai, Shuicheng Yan, Jiashi Feng

MST: Masked Self-Supervised Transformer for Visual Representation Zhaowen Li, Zhiyang Chen, Fan Yang, Wei Li, Yousong Zhu, Chaoyang Zhao, Rui Deng, Liwei Wu, Rui Zhao, Ming Tang, Jinqiao Wang

Exploiting Opponents Under Utility Constraints in Sequential Games Martino Bernasconi-de-Luca, Federico Cacciamani, Simone Fioravanti, Nicola Gatti, Alberto Marchesi, Francesco Trovò

Demystifying and Generalizing BinaryConnect Tim Dockhorn, Yaoliang Yu, Eyyüb Sari, Mahdi Zolnouri, Vahid Partovi Nia

Towards Stable and Robust AdderNets Minjing Dong, Yunhe Wang, Xinghao Chen, Chang Xu

Representing Long-Range Context for Graph Neural Networks with Global Attention Zhanghao Wu, Paras Jain, Matthew Wright, Azalia Mirhoseini, Joseph E Gonzalez, Ion Stoica

Learning Student-Friendly Teacher Networks for Knowledge Distillation Dae Young Park, Moon-Hyun Cha, changwook jeong, Daesin Kim, Bohyung Han

Progressive Coordinate Transforms for Monocular 3D Object Detection Li Wang, Li Zhang, Yi Zhu, Zhi Zhang, Tong He, Mu Li, Xiangyang Xue

Detecting Anomalous Event Sequences with Temporal Point Processes Oleksandr Shchur, Ali Caner Turkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann

HNPE: Leveraging Global Parameters for Neural Posterior Estimation Pedro Rodrigues, Thomas Moreau, Gilles Louppe, Alexandre Gramfort

Alignment Attention by Matching Key and Query Distributions Shujian Zhang, Xinjie Fan, Huangjie Zheng, Korawat Tanwisuth, Mingyuan Zhou

Settling the Variance of Multi-Agent Policy Gradients Jakub Grudzien Kuba, Muning Wen, Linghui Meng, shangding gu, Haifeng Zhang, David Mguni, Jun Wang, Yaodong Yang

Heuristic-Guided Reinforcement Learning Ching-An Cheng, Andrey Kolobov, Adith Swaminathan

Revisiting Smoothed Online Learning Lijun Zhang, Wei Jiang, Shiyin Lu, Tianbao Yang

Marginalised Gaussian Processes with Nested Sampling Fergus Simpson, Vidhi Lalchand, Carl Edward Rasmussen

Bayesian Bellman Operators Mattie Fellows, Kristian Hartikainen, Shimon Whiteson

Uncertainty Calibration for Ensemble-Based Debiasing Methods Ruibin Xiong, Yimeng Chen, Liang Pang, Xueqi Cheng, Zhi-Ming Ma, Yanyan Lan

Test-time Collective Prediction Celestine Mendler-Dünner, Wenshuo Guo, Stephen Bates, Michael I. Jordan

A Continuous Mapping For Augmentation Design Keyu Tian, Chen Lin, Ser Nam Lim, Wanli Ouyang, Puneet Dokania, Philip Torr

Neural Routing by Memory Kaipeng Zhang, Zhenqiang Li, Zhifeng Li, Wei Liu, Yoichi Sato

GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles Octavian Ganea, Lagnajit Pattanaik, Connor Coley, Regina Barzilay, Klavs Jensen, William Green, Tommi Jaakkola

Drop-DTW: Aligning Common Signal Between Sequences While Dropping Outliers Mikita Dvornik, Isma Hadji, Konstantinos G. Derpanis, Animesh Garg, Allan D. Jepson

Safe Reinforcement Learning with Natural Language Constraints Tsung-Yen Yang, Michael Y Hu, Yinlam Chow, Peter J Ramadge, Karthik Narasimhan

ToAlign: Task-Oriented Alignment for Unsupervised Domain Adaptation Guoqiang Wei, Cuiling Lan, Wenjun Zeng, Zhizheng Zhang, Zhibo Chen

Contrastive Active Inference Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt

Dimension-free empirical entropy estimation Doron Cohen, Aryeh Kontorovich, Aaron Koolyk, Geoffrey Wolfer

Towards Biologically Plausible Convolutional Networks Roman Pogodin, Yash Mehta, Timothy Lillicrap, Peter E Latham

DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification Yongming Rao, Wenliang Zhao, Benlin Liu, Jiwen Lu, Jie Zhou, Cho-Jui Hsieh

CLIP-It! Language-Guided Video Summarization Medhini Narasimhan, Anna Rohrbach, Trevor Darrell

Lossy Compression for Lossless Prediction Yann Dubois, Benjamin Bloem-Reddy, Karen Ullrich, Chris J Maddison

CCVS: Context-aware Controllable Video Synthesis Guillaume Le Moing, Jean Ponce, Cordelia Schmid

Predify: Augmenting deep neural networks with brain-inspired predictive coding dynamics Bhavin Choksi, Milad Mozafari, Callum Biggs O'May, B. ADOR, Andrea Alamia, Rufin VanRullen

Generalized DataWeighting via Class-Level Gradient Manipulation Can Chen, Shuhao Zheng, Xi Chen, Erqun Dong, Xue (Steve) Liu, Hao Liu, Dejing Dou

Compressed Video Contrastive Learning Yuqi Huo, Mingyu Ding, Haoyu Lu, Nanyi Fei, Zhiwu Lu, Ji-Rong Wen, Ping Luo

Attention Bottlenecks for Multimodal Fusion Arsha Nagrani, Shan Yang, Anurag Arnab, Aren Jansen, Cordelia Schmid, Chen Sun

Co-evolution Transformer for Protein Contact Prediction He Zhang, Fusong Ju, Jianwei Zhu, Liang He, Bin Shao, Nanning Zheng, Tie-Yan Liu

Unsupervised Foreground Extraction via Deep Region Competition Peiyu Yu, Sirui Xie, Xiaojian Ma, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu

Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation Divyansh Jhunjhunwala, Ankur Mallick, Advait Gadhikar, Swanand Kadhe, Gauri Joshi

Class-Incremental Learning via Dual Augmentation Fei Zhu, Zhen Cheng, Xu-yao Zhang, Cheng-lin Liu

Fair Clustering Under a Bounded Cost Seyed Esmaeili, Brian Brubach, Aravind Srinivasan, John Dickerson

Credal Self-Supervised Learning Julian Lienen, Eyke Hüllermeier

A PAC-Bayes Analysis of Adversarial Robustness Paul Viallard, Eric Guillaume VIDOT, Amaury Habrard, Emilie Morvant

SE(3)-equivariant prediction of molecular wavefunctions and electronic densities Oliver Unke, Mihail Bogojeski, Michael Gastegger, Mario Geiger, Tess Smidt, Klaus-Robert Müller

Modified Frank Wolfe in Probability Space Carson Kent, Jiajin Li, Jose Blanchet, Peter W Glynn

Collaborating with Humans without Human Data DJ Strouse, Kevin McKee, Matt Botvinick, Edward Hughes, Richard Everett

Online Selective Classification with Limited Feedback Aditya Gangrade, Anil Kag, Ashok Cutkosky, Venkatesh Saligrama

Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark Alexander Korotin, Lingxiao Li, Aude Genevay, Justin M Solomon, Alexander Filippov, Evgeny Burnaev

Hard-Attention for Scalable Image Classification Athanasios Papadopoulos, Pawel Korus, Nasir Memon

Data driven semi-supervised learning Maria-Florina F Balcan, Dravyansh Sharma

Characterizing the risk of fairwashing Ulrich Aïvodji, Hiromi Arai, Sébastien Gambs, Satoshi Hara

Graph Adversarial Self-Supervised Learning Longqi Yang, Liangliang Zhang, Wenjing Yang

Anti-Backdoor Learning: Training Clean Models on Poisoned Data Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Xingjun Ma

Robust Compressed Sensing MRI with Deep Generative Priors Ajil Jalal, Marius Arvinte, Giannis Daras, ecprice, Alexandros G Dimakis, Jon Tamir

DOBF: A Deobfuscation Pre-Training Objective for Programming Languages Marie-Anne Lachaux, Baptiste Roziere, Marc Szafraniec, Guillaume Lample

Learning-to-learn non-convex piecewise-Lipschitz functions Maria-Florina F Balcan, Mikhail Khodak, Dravyansh Sharma, Ameet Talwalkar

Decision Transformer: Reinforcement Learning via Sequence Modeling Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Misha Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch

CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks Sakshi Varshney, Vinay Kumar Verma, P. K. Srijith, Lawrence Carin, Piyush Rai

Structured Dropout Variational Inference for Bayesian Neural Networks Son Nguyen, Duong Nguyen, Khai Nguyen, Khoat Than, Hung Bui, Nhat Ho

Learning to Ground Multi-Agent Communication with Autoencoders Toru Lin, Jacob Huh, Christopher Stauffer, Ser Nam Lim, Phillip Isola

Large-Scale Wasserstein Gradient Flows Petr Mokrov, Alexander Korotin, Lingxiao Li, Aude Genevay, Justin M Solomon, Evgeny Burnaev

Who Leads and Who Follows in Strategic Classification? Tijana Zrnic, Eric Mazumdar, Shankar Sastry, Michael I. Jordan

Unadversarial Examples: Designing Objects for Robust Vision Hadi Salman, Andrew Ilyas, Logan Engstrom, Sai Vemprala, Aleksander Madry, Ashish Kapoor

Augmented Shortcuts for Vision Transformers Yehui Tang, Kai Han, Chang Xu, An Xiao, Yiping Deng, Chao Xu, Yunhe Wang

Label Disentanglement in Partition-based Extreme Multilabel Classification Xuanqing Liu, Wei-Cheng Chang, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon

Neural Circuit Synthesis from Specification Patterns Frederik Schmitt, Christopher Hahn, Markus N Rabe, Bernd Finkbeiner

Federated Multi-Task Learning under a Mixture of Distributions Othmane Marfoq, Giovanni Neglia, Aurélien Bellet, Laetitia Kameni, Richard Vidal

Adversarially Robust 3D Point Cloud Recognition Using Self-Supervisions Jiachen Sun, Yulong Cao, Christopher B Choy, Zhiding Yu, Anima Anandkumar, Zhuoqing Morley Mao, Chaowei Xiao

Neural Algorithmic Reasoners are Implicit Planners Andreea-Ioana Deac, Petar Veličković, Ognjen Milinkovic, Pierre-Luc Bacon, Jian Tang, Mladen Nikolic

Self-Supervised Learning with Kernel Dependence Maximization Yazhe Li, Roman Pogodin, Danica J. Sutherland, Arthur Gretton

Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception Joel Dapello, Jenelle Feather, Hang Le, Tiago Marques, David Cox, Josh McDermott, James J DiCarlo, Sueyeon Chung

Unsupervised Learning of Compositional Energy Concepts Yilun Du, Shuang Li, Yash Sharma, Josh Tenenbaum, Igor Mordatch

Nearly Horizon-Free Offline Reinforcement Learning Tongzheng Ren, Jialian Li, Bo Dai, Simon S Du, Sujay Sanghavi

Iterative Amortized Policy Optimization Joseph Marino, Alexandre Piche, Alessandro Davide Ialongo, Yisong Yue

Revisiting the Calibration of Modern Neural Networks Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic

FLEX: Unifying Evaluation for Few-Shot NLP Jonathan Bragg, Arman Cohan, Kyle Lo, Iz Beltagy

A flow-based latent state generative model of neural population responses to natural images Mohammad Bashiri, Edgar Walker, Konstantin-Klemens Lurz, Akshay Jagadish, Taliah Muhammad, Zhiwei Ding, Zhuokun Ding, Andreas Tolias, Fabian H. Sinz

Rethinking Neural Operations for Diverse Tasks Nicholas Roberts, Mikhail Khodak, Tri Dao, Liam Li, Christopher Ré, Ameet Talwalkar

Transformer in Transformer Kai Han, An Xiao, Enhua Wu, Jianyuan Guo, Chunjing XU, Yunhe Wang

Online Control of Unknown Time-Varying Dynamical Systems Edgar Minasyan, Paula Gradu, Max Simchowitz, Elad Hazan

Recurrent Bayesian Classifier Chains for Exact Multi-Label Classification Walter Gerych, Tom Hartvigsen, Luke Buquicchio, Emmanuel Agu, Elke A. Rundensteiner

Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang, Tianyun Zhang, Sijia Liu, Pin-Yu Chen, Jiacen Xu, Makan Fardad, Bo Li

Safe Pontryagin Differentiable Programming Wanxin Jin, Shaoshuai Mou, George J. Pappas

Active 3D Shape Reconstruction from Vision and Touch Edward Smith, David Meger, Luis Pineda, Roberto Calandra, Jitendra Malik, Adriana Romero Soriano, Michal Drozdzal

CAPE: Encoding Relative Positions with Continuous Augmented Positional Embeddings Tatiana Likhomanenko, Qiantong Xu, Gabriel Synnaeve, Ronan Collobert, Alex Rogozhnikov

Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning Xinyi Xu, Lingjuan Lyu, Xingjun Ma, Chenglin Miao, Chuan Sheng Foo, Bryan Kian Hsiang Low

Learning Diverse Policies in MOBA Games via Macro-Goals Yiming Gao, Bei Shi, Xueying Du, Liang Wang, Guangwei Chen, Zhenjie Lian, Fuhao Qiu, GUOAN HAN, Weixuan Wang, Deheng Ye, Qiang Fu, Wei Yang, Lanxiao Huang

Evaluation of Human-AI Teams for Learned and Rule-Based Agents in Hanabi Ho Chit Siu, Jaime Peña, Edenna Chen, Yutai Zhou, Victor Lopez, Kyle Palko, Kimberlee Chang, Ross Allen

Diffusion Normalizing Flow Qinsheng Zhang, Yongxin Chen

Rethinking the Pruning Criteria for Convolutional Neural Network Zhongzhan Huang, Wenqi Shao, Xinjiang Wang, Liang Lin, Ping Luo

EditGAN: High-Precision Semantic Image Editing Huan Ling, Karsten Kreis, Daiqing Li, Seung Wook Kim, Antonio Torralba, Sanja Fidler

Neural optimal feedback control with local learning rules Johannes Friedrich, Siavash Golkar, Shiva Farashahi, Alexander Genkin, Anirvan Sengupta, Dmitri B. Chklovskii

Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection Matteo Papini, Andrea Tirinzoni, Aldo Pacchiano, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta

Noether Networks: meta-learning useful conserved quantities Ferran Alet, Dylan Doblar, Allan Zhou, Josh Tenenbaum, Kenji Kawaguchi, Chelsea Finn

Uncertainty-Driven Loss for Single Image Super-Resolution Qian Ning, Weisheng Dong, Xin Li, Jinjian Wu, GUANGMING Shi

Capacity and Bias of Learned Geometric Embeddings for Directed Graphs Michael Boratko, Dongxu Zhang, Nicholas Monath, Luke Vilnis, Kenneth L Clarkson, Andrew McCallum

Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style Julius von Kügelgen, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf, Michel Besserve, Francesco Locatello

Instance-Conditional Knowledge Distillation for Object Detection Zijian Kang, Peizhen Zhang, Xiangyu Zhang, Jian Sun, Nanning Zheng

Multimodal Virtual Point 3D Detection Tianwei Yin, Xingyi Zhou, Philipp Krähenbühl

Learning with Algorithmic Supervision via Continuous Relaxations Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen

Differentiable Multiple Shooting Layers Stefano Massaroli, Michael Poli, Sho Sonoda, Taiji Suzuki, Jinkyoo Park, Atsushi Yamashita, Hajime Asama

Few-Shot Object Detection via Association and DIscrimination Yuhang Cao, Jiaqi Wang, Ying Jin, Tong Wu, Kai Chen, Ziwei Liu, Dahua Lin

Neural Dubber: Dubbing for Videos According to Scripts Chenxu Hu, Qiao Tian, Tingle Li, Wang Yuping, Yuxuan Wang, Hang Zhao

Neural Bootstrapper Minsuk Shin, Hyungjoo Cho, Hyun-seok Min, Sungbin Lim

HSVA: Hierarchical Semantic-Visual Adaptation for Zero-Shot Learning Shiming Chen, Guosen Xie, Yang Liu, Qinmu Peng, Baigui Sun, Hao Li, Xinge You, Ling Shao

Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes Cristopher Salvi, Maud Lemercier, Chong Liu, Blanka Horvath, Theodoros Damoulas, Terry Lyons

Large-Scale Unsupervised Object Discovery Van Huy Vo, Elena Sizikova, Cordelia Schmid, Patrick Pérez, Jean Ponce

Joint inference and input optimization in equilibrium networks Swaminathan Gurumurthy, Shaojie Bai, Zachary Manchester, J. Zico Kolter

Recovering Latent Causal Factor for Generalization to Distributional Shifts Xinwei Sun, Botong Wu, Xiangyu Zheng, Chang Liu, Wei Chen, Tao Qin, Tie-Yan Liu

Designing Counterfactual Generators using Deep Model Inversion Jayaraman Thiagarajan, Vivek Sivaraman Narayanaswamy, Deepta Rajan, Jia Liang, Akshay Chaudhari, Andreas Spanias

Towards Robust and Reliable Algorithmic Recourse Sohini Upadhyay, Shalmali Joshi, Himabindu Lakkaraju

Neural Rule-Execution Tracking Machine For Transformer-Based Text Generation Yufei Wang, Can Xu, Huang Hu, Chongyang Tao, Stephen Wan, Mark Dras, Mark Johnson, Daxin Jiang

Scalable Online Planning via Reinforcement Learning Fine-Tuning Arnaud Fickinger, Hengyuan Hu, Brandon Amos, Stuart J. Russell, Noam Brown

Adversarial Regression with Doubly Non-negative Weighting Matrices Tam Le, Truyen Nguyen, Makoto Yamada, Jose Blanchet, Viet Anh Nguyen

Dynamic Bottleneck for Robust Self-Supervised Exploration Chenjia Bai, Lingxiao Wang, Lei Han, Animesh Garg, Jianye Hao, Peng Liu, Zhaoran Wang

An Efficient Transfer Learning Framework for Multiagent Reinforcement Learning Tianpei Yang, Weixun Wang, Hongyao Tang, Jianye Hao, Zhaopeng Meng, Hangyu Mao, Dong Li, Wulong Liu, Yingfeng Chen, Yujing Hu, Changjie Fan, Chengwei Zhang

NEO: Non Equilibrium Sampling on the Orbits of a Deterministic Transform Achille Thin, Yazid Janati El Idrissi, Sylvain Le Corff, Charles Ollion, Eric Moulines, Arnaud Doucet, Alain Durmus, Christian X Robert

Relaxing Local Robustness Klas Leino, Matt Fredrikson

Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer Ge Yang, Edward Hu, Igor Babuschkin, Szymon Sidor, Xiaodong Liu, David Farhi, Nick Ryder, Jakub Pachocki, Weizhu Chen, Jianfeng Gao

Differentiable Simulation of Soft Multi-body Systems Yiling Qiao, Junbang Liang, Vladlen Koltun, Ming Lin

Good Classification Measures and How to Find Them Martijn Gösgens, Anton Zhiyanov, Aleksey Tikhonov, Liudmila Prokhorenkova

Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels Michael Hutchinson, Alexander Terenin, Viacheslav Borovitskiy, So Takao, Yee W. Teh, Marc Deisenroth

A Prototype-Oriented Framework for Unsupervised Domain Adaptation Korawat Tanwisuth, Xinjie Fan, Huangjie Zheng, Shujian Zhang, Hao Zhang, Bo Chen, Mingyuan Zhou

Mining the Benefits of Two-stage and One-stage HOI Detection Aixi Zhang, Yue Liao, Si Liu, Miao Lu, Yongliang Wang, Chen Gao, XIAOBO LI

Risk-averse Heteroscedastic Bayesian Optimization Anastasia Makarova, Ilnura Usmanova, Ilija Bogunovic, Andreas Krause

Invertible DenseNets with Concatenated LipSwish Yura Perugachi-Diaz, Jakub Tomczak, Sandjai Bhulai

Topological Detection of Trojaned Neural Networks Songzhu Zheng, Yikai Zhang, Hubert Wagner, Mayank Goswami, Chao Chen

Causal Inference for Event Pairs in Multivariate Point Processes Tian Gao, Dharmashankar Subramanian, Debarun Bhattacharjya, Xiao Shou, Nicholas Mattei, Kristin P Bennett

Coresets for Clustering with Missing Values Vladimir Braverman, Shaofeng Jiang, Robert Krauthgamer, Xuan Wu

Boosting with Multiple Sources Corinna Cortes, Mehryar Mohri, Dmitry Storcheus, Ananda Theertha Suresh

Dense Keypoints via Multiview Supervision Zhixuan Yu, Haozheng Yu, Long Sha, Sujoy Ganguly, Hyun Soo Park

Scatterbrain: Unifying Sparse and Low-rank Attention Beidi Chen, Tri Dao, Eric Winsor, Zhao Song, Atri Rudra, Christopher Ré

Differentially Private Learning with Adaptive Clipping Galen Andrew, Om Thakkar, Brendan McMahan, Swaroop Ramaswamy

Projected GANs Converge Faster Axel Sauer, Kashyap Chitta, Jens Müller, Andreas Geiger

Hash Layers For Large Sparse Models Stephen Roller, Sainbayar Sukhbaatar, arthur szlam, Jason Weston

Regret Minimization Experience Replay in Off-Policy Reinforcement Learning Xu-Hui Liu, Zhenghai Xue, Jingcheng Pang, Shengyi Jiang, Feng Xu, Yang Yu

TRS: Transferability Reduced Ensemble via Promoting Gradient Diversity and Model Smoothness Zhuolin Yang, Linyi Li, Xiaojun Xu, Shiliang Zuo, Qian Chen, Pan Zhou, Benjamin I. Rubinstein, Ce Zhang, Bo Li

Structure-Aware Random Fourier Kernel for Graphs Jinyuan Fang, Qiang Zhang, Zaiqiao Meng, Shangsong Liang

Long-Short Transformer: Efficient Transformers for Language and Vision Chen Zhu, Wei Ping, Chaowei Xiao, Mohammad Shoeybi, Tom Goldstein, Anima Anandkumar, Bryan Catanzaro

Post-Training Sparsity-Aware Quantization Gil Shomron, Freddy Gabbay, Samer Kurzum, Uri Weiser

Robust Auction Design in the Auto-bidding World Santiago Balseiro, Yuan Deng, Jieming Mao, Vahab Mirrokni, Song Zuo

Image Generation using Continuous Filter Atoms Ze Wang, Seunghyun Hwang, Zichen Miao, Qiang Qiu

Learning Fast-Inference Bayesian Networks Vaidyanathan Peruvemba Ramaswamy, Stefan Szeider

MOMA: Multi-Object Multi-Actor Activity Parsing Zelun Luo, Wanze Xie, Siddharth Kapoor, Yiyun Liang, Michael Cooper, Juan Carlos Niebles, Ehsan Adeli, Fei-Fei Li

Structured Denoising Diffusion Models in Discrete State-Spaces Jacob Austin, Daniel D. Johnson, Jonathan Ho, Daniel Tarlow, Rianne van den Berg

Manipulating SGD with Data Ordering Attacks I Shumailov, Zakhar Shumaylov, Dmitry Kazhdan, Yiren Zhao, Nicolas Papernot, Murat A Erdogdu, Ross J Anderson

Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification Maximilian Stadler, Bertrand Charpentier, Simon Geisler, Daniel Zügner, Stephan Günnemann

No-Press Diplomacy from Scratch Anton Bakhtin, David Wu, Adam Lerer, Noam Brown

Remember What You Want to Forget: Algorithms for Machine Unlearning Ayush Sekhari, Jayadev Acharya, Gautam Kamath, Ananda Theertha Suresh

Learning latent causal graphs via mixture oracles Bohdan Kivva, Goutham Rajendran, Pradeep K. Ravikumar, Bryon Aragam

Learning curves of generic features maps for realistic datasets with a teacher-student model Bruno Loureiro, Cedric Gerbelot, Hugo Cui, Sebastian Goldt, Florent Krzakala, Marc Mezard, Lenka Zdeborová

Reinforcement learning for optimization of variational quantum circuit architectures Mateusz Ostaszewski, Lea M. Trenkwalder, Wojciech Masarczyk, Eleanor Scerri, Vedran Dunjko