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Widening the Pipeline in Human-Guided Reinforcement Learning with Explanation and Context-Aware Data Augmentation
Lin Guan · Mudit Verma · Sihang Guo · Ruohan Zhang · Subbarao Kambhampati
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PLUR: A Unifying, Graph-Based View of Program Learning, Understanding, and Repair
Zimin Chen · Vincent J Hellendoorn · Pascal Lamblin · Petros Maniatis · Pierre-Antoine Manzagol · Daniel Tarlow · Subhodeep Moitra
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Numerical Composition of Differential Privacy
Sivakanth Gopi · Yin Tat Lee · Lukas Wutschitz
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Neural Symplectic Form: Learning Hamiltonian Equations on General Coordinate Systems
Yuhan Chen · Takashi Matsubara · Takaharu Yaguchi
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Information Directed Sampling for Sparse Linear Bandits
Botao Hao · Tor Lattimore · Wei Deng
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Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima
Guangyuan SHI · JIAXIN CHEN · Wenlong Zhang · Li-Ming Zhan · Xiao-Ming Wu
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Subgaussian and Differentiable Importance Sampling for Off-Policy Evaluation and Learning
Alberto Maria Metelli · Alessio Russo · Marcello Restelli
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Statistical Regeneration Guarantees of the Wasserstein Autoencoder with Latent Space Consistency
Anish Chakrabarty · Swagatam Das
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Neural Additive Models: Interpretable Machine Learning with Neural Nets
Rishabh Agarwal · Levi Melnick · Nicholas Frosst · Xuezhou Zhang · Ben Lengerich · Rich Caruana · Geoffrey Hinton
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Learning to Compose Visual Relations
Nan Liu · Shuang Li · Yilun Du · Josh Tenenbaum · Antonio Torralba
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Bootstrapping the Error of Oja's Algorithm
Robert Lunde · Purnamrita Sarkar · Rachel Ward
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Doubly Robust Thompson Sampling with Linear Payoffs
Wonyoung Kim · Gi-Soo Kim · Myunghee Cho Paik
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Differentially Private Model Personalization
Prateek Jain · John Rush · Adam Smith · Shuang Song · Abhradeep Guha Thakurta
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Counterfactual Invariance to Spurious Correlations in Text Classification
Victor Veitch · Alexander D'Amour · Steve Yadlowsky · Jacob Eisenstein
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SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression
Steve Yadlowsky · Taedong Yun · Cory Y McLean · Alexander D'Amour
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Optimal Policies Tend To Seek Power
Alex Turner · Logan Smith · Rohin Shah · Andrew Critch · Prasad Tadepalli
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Variational Inference for Continuous-Time Switching Dynamical Systems
Lukas Köhs · Bastian Alt · Heinz Koeppl
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Task-Adaptive Neural Network Search with Meta-Contrastive Learning
Wonyong Jeong · Hayeon Lee · Geon Park · Eunyoung Hyung · Jinheon Baek · Sung Ju Hwang
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Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning
Yiqin Yang · Xiaoteng Ma · Li Chenghao · Zewu Zheng · Qiyuan Zhang · Gao Huang · Jun Yang · Qianchuan Zhao
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Online Active Learning with Surrogate Loss Functions
Giulia DeSalvo · Claudio Gentile · Tobias Sommer Thune
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Subgroup Generalization and Fairness of Graph Neural Networks
Jiaqi Ma · Junwei Deng · Qiaozhu Mei
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Profiling Pareto Front With Multi-Objective Stein Variational Gradient Descent
Xingchao Liu · Xin Tong · Qiang Liu
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An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence
Agustinus Kristiadi · Matthias Hein · Philipp Hennig
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RIM: Reliable Influence-based Active Learning on Graphs
Wentao Zhang · Yexin Wang · Zhenbang You · Meng Cao · Ping Huang · Jiulong Shan · Zhi Yang · Bin CUI
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Program Synthesis Guided Reinforcement Learning for Partially Observed Environments
Yichen Yang · Jeevana Priya Inala · Osbert Bastani · Yewen Pu · Armando Solar-Lezama · Martin Rinard
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On Inductive Biases for Heterogeneous Treatment Effect Estimation
Alicia Curth · Mihaela van der Schaar
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Iteratively Reweighted Least Squares for Basis Pursuit with Global Linear Convergence Rate
Christian Kümmerle · Claudio Mayrink Verdun · Dominik Stöger
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Unintended Selection: Persistent Qualification Rate Disparities and Interventions
Reilly Raab · Yang Liu
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Learning to See by Looking at Noise
Manel Baradad · Jonas Wulff · Tongzhou Wang · Phillip Isola · Antonio Torralba
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Learning with Holographic Reduced Representations
Ashwinkumar Ganesan · Hang Gao · Sunil Gandhi · Edward Raff · Tim Oates · James Holt · Mark McLean
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Offline RL Without Off-Policy Evaluation
David Brandfonbrener · William Whitney · Rajesh Ranganath · Joan Bruna
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Sliced Mutual Information: A Scalable Measure of Statistical Dependence
Ziv Goldfeld · Kristjan Greenewald
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On the Power of Differentiable Learning versus PAC and SQ Learning
Emmanuel Abbe · Pritish Kamath · Eran Malach · Colin Sandon · Nathan Srebro
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Online and Offline Reinforcement Learning by Planning with a Learned Model
Julian Schrittwieser · Thomas Hubert · Amol Mandhane · Mohammadamin Barekatain · Ioannis Antonoglou · David Silver
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Reward is enough for convex MDPs
Tom Zahavy · Brendan O'Donoghue · Guillaume Desjardins · Satinder Singh
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Calibration and Consistency of Adversarial Surrogate Losses
Pranjal Awasthi · Natalie Frank · Anqi Mao · Mehryar Mohri · Yutao Zhong
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Process for Adapting Language Models to Society (PALMS) with Values-Targeted Datasets
Irene Solaiman · Christy Dennison
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The Sensory Neuron as a Transformer: Permutation-Invariant Neural Networks for Reinforcement Learning
Yujin Tang · David Ha
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On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method
Junyu Zhang · Chengzhuo Ni · zheng Yu · Csaba Szepesvari · Mengdi Wang
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A Variational Perspective on Diffusion-Based Generative Models and Score Matching
Chin-Wei Huang · Jae Hyun Lim · Aaron Courville
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Constrained Robust Submodular Partitioning
Shengjie Wang · Tianyi Zhou · Chandrashekhar Lavania · Jeff A Bilmes
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Representation Learning Beyond Linear Prediction Functions
Ziping Xu · Ambuj Tewari
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Batch Normalization Orthogonalizes Representations in Deep Random Networks
Hadi Daneshmand · Amir Joudaki · Francis Bach
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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
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Conformal Prediction using Conditional Histograms
Matteo Sesia · Yaniv Romano
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Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits
reda ouhamma · Rémy Degenne · Vianney Perchet · Pierre Gaillard
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A Geometric Analysis of Neural Collapse with Unconstrained Features
Zhihui Zhu · Tianyu Ding · Jinxin Zhou · Xiao Li · Chong You · Jeremias Sulam · Qing Qu
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Lower and Upper Bounds on the Pseudo-Dimension of Tensor Network Models
Behnoush Khavari · Guillaume Rabusseau
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Practical Near Neighbor Search via Group Testing
Joshua Engels · Benjamin Coleman · Anshumali Shrivastava
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Representation Learning for Event-based Visuomotor Policies
Sai Vemprala · Sami Mian · Ashish Kapoor
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Breaking the Dilemma of Medical Image-to-image Translation
Lingke Kong · Chenyu Lian · Detian Huang · zhenjiang li · Yanle Hu · Qichao Zhou
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ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning
Guocheng Qian · Hasan Hammoud · Guohao Li · Ali Thabet · Bernard Ghanem
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A Closer Look at the Worst-case Behavior of Multi-armed Bandit Algorithms
Anand Kalvit · Assaf Zeevi
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A sampling-based circuit for optimal decision making
Camille Rullán Buxó · Cristina Savin
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Covariance-Aware Private Mean Estimation Without Private Covariance Estimation
Gavin Brown · Marco Gaboardi · Adam Smith · Jonathan Ullman · Lydia Zakynthinou
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Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning
Hayeon Lee · Sewoong Lee · Song Chong · Sung Ju Hwang
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H-NeRF: Neural Radiance Fields for Rendering and Temporal Reconstruction of Humans in Motion
Hongyi Xu · Thiemo Alldieck · Cristian Sminchisescu
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Interactive Label Cleaning with Example-based Explanations
Stefano Teso · Andrea Bontempelli · Fausto Giunchiglia · Andrea Passerini
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DiBS: Differentiable Bayesian Structure Learning
Lars Lorch · Jonas Rothfuss · Bernhard Schölkopf · Andreas Krause
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Aligning Pretraining for Detection via Object-Level Contrastive Learning
Fangyun Wei · Yue Gao · Zhirong Wu · Han Hu · Stephen Lin
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Optimal Sketching for Trace Estimation
Shuli Jiang · Hai Pham · David Woodruff · Richard Zhang
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Uniform Sampling over Episode Difficulty
Sébastien Arnold · Guneet Dhillon · Avinash Ravichandran · Stefano Soatto
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Efficient Online Estimation of Causal Effects by Deciding What to Observe
Shantanu Gupta · Zachary Lipton · David Childers
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Double Machine Learning Density Estimation for Local Treatment Effects with Instruments
Yonghan Jung · Jin Tian · Elias Bareinboim
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Efficiently Identifying Task Groupings for Multi-Task Learning
Chris Fifty · Ehsan Amid · Zhe Zhao · Tianhe Yu · Rohan Anil · Chelsea Finn
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Rethinking gradient sparsification as total error minimization
Atal N Sahu · Aritra Dutta · Ahmed M. Abdelmoniem · Trambak Banerjee · Marco Canini · Panos Kalnis
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Speedy Performance Estimation for Neural Architecture Search
Robin Ru · Clare Lyle · Lisa Schut · Miroslav Fil · Mark van der Wilk · Yarin Gal
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Iterative Teaching by Label Synthesis
Weiyang Liu · Zhen Liu · Hanchen Wang · Liam Paull · Bernhard Schölkopf · Adrian Weller
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Refining Language Models with Compositional Explanations
Huihan Yao · Ying Chen · Qinyuan Ye · Xisen Jin · Xiang Ren
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Dense Keypoints via Multiview Supervision
Zhixuan Yu · Haozheng Yu · Long Sha · Sujoy Ganguly · Hyun Park
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Amortized Synthesis of Constrained Configurations Using a Differentiable Surrogate
Xingyuan Sun · Tianju Xue · Szymon Rusinkiewicz · Ryan Adams
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Perturbation-based Regret Analysis of Predictive Control in Linear Time Varying Systems
Yiheng Lin · Yang Hu · Guanya Shi · Haoyuan Sun · Guannan Qu · Adam Wierman
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MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge
Geng Yuan · Xiaolong Ma · Wei Niu · Zhengang Li · Zhenglun Kong · Ning Liu · Yifan Gong · Zheng Zhan · Chaoyang He · Qing Jin · Siyue Wang · Minghai Qin · Bin Ren · Yanzhi Wang · Sijia Liu · Xue Lin
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A Theory-Driven Self-Labeling Refinement Method for Contrastive Representation Learning
Pan Zhou · Caiming Xiong · Xiaotong Yuan · Steven Chu Hong Hoi
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Learning Generalized Gumbel-max Causal Mechanisms
Guy Lorberbom · Daniel D. Johnson · Chris Maddison · Daniel Tarlow · Tamir Hazan
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Neural Human Performer: Learning Generalizable Radiance Fields for Human Performance Rendering
Youngjoong Kwon · Dahun Kim · Duygu Ceylan · Henry Fuchs
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Supercharging Imbalanced Data Learning With Energy-based Contrastive Representation Transfer
Junya Chen · Zidi Xiu · Benjamin Goldstein · Ricardo Henao · Lawrence Carin · Chenyang Tao
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Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications
Leonard Berrada · Sumanth Dathathri · Krishnamurthy Dvijotham · Robert Stanforth · Rudy Bunel · Jonathan Uesato · Sven Gowal · M. Pawan Kumar
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Coresets for Decision Trees of Signals
Ibrahim Jubran · Ernesto Evgeniy Sanches Shayda · Ilan I Newman · Dan Feldman
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Prototypical Cross-Attention Networks for Multiple Object Tracking and Segmentation
Lei Ke · Xia Li · Martin Danelljan · Yu-Wing Tai · Chi-Keung Tang · Fisher Yu
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Beyond Tikhonov: faster learning with self-concordant losses, via iterative regularization
Gaspard Beugnot · Julien Mairal · Alessandro Rudi
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Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks
Hassan Dbouk · Naresh Shanbhag
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Improved Coresets and Sublinear Algorithms for Power Means in Euclidean Spaces
Vincent Cohen-Addad · David Saulpic · Chris Schwiegelshohn
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Online Selective Classification with Limited Feedback
Aditya Gangrade · Anil Kag · Ashok Cutkosky · Venkatesh Saligrama
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Node Dependent Local Smoothing for Scalable Graph Learning
Wentao Zhang · Mingyu Yang · Zeang Sheng · Yang Li · Wen Ouyang · Yangyu Tao · Zhi Yang · Bin CUI
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Spherical Motion Dynamics: Learning Dynamics of Normalized Neural Network using SGD and Weight Decay
Ruosi Wan · Zhanxing Zhu · Xiangyu Zhang · Jian Sun
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Auditing Black-Box Prediction Models for Data Minimization Compliance
Bashir Rastegarpanah · Krishna Gummadi · Mark Crovella
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DOCTOR: A Simple Method for Detecting Misclassification Errors
Federica Granese · Marco Romanelli · Daniele Gorla · Catuscia Palamidessi · Pablo Piantanida
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Closing the Gap: Tighter Analysis of Alternating Stochastic Gradient Methods for Bilevel Problems
Tianyi Chen · Yuejiao Sun · Wotao Yin
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A Geometric Perspective towards Neural Calibration via Sensitivity Decomposition
Junjiao Tian · Dylan Yung · Yen-Chang Hsu · Zsolt Kira
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Shaping embodied agent behavior with activity-context priors from egocentric video
Tushar Nagarajan · Kristen Grauman
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Self-Supervised Learning Disentangled Group Representation as Feature
Tan Wang · Zhongqi Yue · Jianqiang Huang · Qianru Sun · Hanwang Zhang
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The Semi-Random Satisfaction of Voting Axioms
Lirong Xia
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Multiwavelet-based Operator Learning for Differential Equations
Gaurav Gupta · Xiongye Xiao · Paul Bogdan
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The functional specialization of visual cortex emerges from training parallel pathways with self-supervised predictive learning
Shahab Bakhtiari · Patrick Mineault · Timothy Lillicrap · Christopher Pack · Blake Richards
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Excess Capacity and Backdoor Poisoning
Naren Manoj · Avrim Blum
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Behavior From the Void: Unsupervised Active Pre-Training
Hao Liu · Pieter Abbeel
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Exploration-Exploitation in Multi-Agent Competition: Convergence with Bounded Rationality
Stefanos Leonardos · Georgios Piliouras · Kelly Spendlove
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Provably Faster Algorithms for Bilevel Optimization
Junjie Yang · Kaiyi Ji · Yingbin Liang
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Finding Discriminative Filters for Specific Degradations in Blind Super-Resolution
Liangbin Xie · Xintao Wang · Chao Dong · Zhongang Qi · Ying Shan
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Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling
Valentin De Bortoli · James Thornton · Jeremy Heng · Arnaud Doucet
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Correlated Stochastic Block Models: Exact Graph Matching with Applications to Recovering Communities
Miklos Racz · Anirudh Sridhar
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NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction
Peng Wang · Lingjie Liu · Yuan Liu · Christian Theobalt · Taku Komura · Wenping Wang
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A Minimalist Approach to Offline Reinforcement Learning
Scott Fujimoto · Shixiang (Shane) Gu
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Offline Reinforcement Learning as One Big Sequence Modeling Problem
Michael Janner · Qiyang Li · Sergey Levine
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Second-Order Neural ODE Optimizer
Guan-Horng Liu · Tianrong Chen · Evangelos Theodorou
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Foundations of Symbolic Languages for Model Interpretability
Marcelo Arenas · Daniel Báez · Pablo Barceló · Jorge Pérez · Bernardo Subercaseaux
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Differential Privacy Dynamics of Langevin Diffusion and Noisy Gradient Descent
Rishav Chourasia · Jiayuan Ye · Reza Shokri
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Image Generation using Continuous Filter Atoms
Ze Wang · Seunghyun Hwang · Zichen Miao · Qiang Qiu
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A Unified Approach to Fair Online Learning via Blackwell Approachability
Evgenii Chzhen · Christophe Giraud · Gilles Stoltz
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Repulsive Deep Ensembles are Bayesian
Francesco D'Angelo · Vincent Fortuin
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Lossy Compression for Lossless Prediction
Yann Dubois · Benjamin Bloem-Reddy · Karen Ullrich · Chris Maddison
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Redesigning the Transformer Architecture with Insights from Multi-particle Dynamical Systems
Subhabrata Dutta · Tanya Gautam · Soumen Chakrabarti · Tanmoy Chakraborty
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Habitat 2.0: Training Home Assistants to Rearrange their Habitat
Andrew Szot · Alexander Clegg · Eric Undersander · Erik Wijmans · Yili Zhao · John Turner · Noah Maestre · Mustafa Mukadam · Devendra Singh Chaplot · Oleksandr Maksymets · Aaron Gokaslan · Vladimír Vondruš · Sameer Dharur · Franziska Meier · Wojciech Galuba · Angel Chang · Zsolt Kira · Vladlen Koltun · Jitendra Malik · Manolis Savva · Dhruv Batra
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Mind the Gap: Assessing Temporal Generalization in Neural Language Models
Angeliki Lazaridou · Adhi Kuncoro · Elena Gribovskaya · Devang Agrawal · Adam Liska · Tayfun Terzi · Mai Gimenez · Cyprien de Masson d'Autume · Tomas Kocisky · Sebastian Ruder · Dani Yogatama · Kris Cao · Susannah Young · Phil Blunsom
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IQ-Learn: Inverse soft-Q Learning for Imitation
Divyansh Garg · Shuvam Chakraborty · Chris Cundy · Jiaming Song · Stefano Ermon
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Forster Decomposition and Learning Halfspaces with Noise
Ilias Diakonikolas · Daniel Kane · Christos Tzamos
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Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret
Jean Tarbouriech · Runlong Zhou · Simon Du · Matteo Pirotta · Michal Valko · Alessandro Lazaric
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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
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ViSER: Video-Specific Surface Embeddings for Articulated 3D Shape Reconstruction
Gengshan Yang · Deqing Sun · Varun Jampani · Daniel Vlasic · Forrester Cole · Ce Liu · Deva Ramanan
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Clustering Effect of Adversarial Robust Models
Yang Bai · Xin Yan · Yong Jiang · Shu-Tao Xia · Yisen Wang
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Exact marginal prior distributions of finite Bayesian neural networks
Jacob Zavatone-Veth · Cengiz Pehlevan
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Fair Sparse Regression with Clustering: An Invex Relaxation for a Combinatorial Problem
Adarsh Barik · Jean Honorio
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Across-animal odor decoding by probabilistic manifold alignment
Pedro Herrero-Vidal · Dmitry Rinberg · Cristina Savin
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Your head is there to move you around: Goal-driven models of the primate dorsal pathway
Patrick Mineault · Shahab Bakhtiari · Blake Richards · Christopher Pack
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A Normative and Biologically Plausible Algorithm for Independent Component Analysis
Yanis Bahroun · Dmitri Chklovskii · Anirvan Sengupta
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Learning Large Neighborhood Search Policy for Integer Programming
Yaoxin Wu · Wen Song · Zhiguang Cao · Jie Zhang
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Long Short-Term Transformer for Online Action Detection
Mingze Xu · Yuanjun Xiong · Hao Chen · Xinyu Li · Wei Xia · Zhuowen Tu · Stefano Soatto
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Is Automated Topic Model Evaluation Broken? The Incoherence of Coherence
Alexander Hoyle · Pranav Goel · Andrew Hian-Cheong · Denis Peskov · Jordan Boyd-Graber · Philip Resnik
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Fast Bayesian Inference for Gaussian Cox Processes via Path Integral Formulation
Hideaki Kim
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A Provably Efficient Sample Collection Strategy for Reinforcement Learning
Jean Tarbouriech · Matteo Pirotta · Michal Valko · Alessandro Lazaric
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PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition
Cheng-I Jeff Lai · Yang Zhang · Alexander Liu · Shiyu Chang · Yi-Lun Liao · Yung-Sung Chuang · Kaizhi Qian · Sameer Khurana · David Cox · Jim Glass
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Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent
Jason Altschuler · Sinho Chewi · Patrik R Gerber · Austin J Stromme
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Adversarial Teacher-Student Representation Learning for Domain Generalization
Fu-En Yang · Yuan-Chia Cheng · Zu-Yun Shiau · Yu-Chiang Frank Wang
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Baleen: Robust Multi-Hop Reasoning at Scale via Condensed Retrieval
Omar Khattab · Christopher Potts · Matei Zaharia
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Pragmatic Image Compression for Human-in-the-Loop Decision-Making
Sid Reddy · Anca Dragan · Sergey Levine
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SOFT: Softmax-free Transformer with Linear Complexity
Jiachen Lu · Jinghan Yao · Junge Zhang · Xiatian Zhu · Hang Xu · Weiguo Gao · Chunjing XU · Tao Xiang · Li Zhang
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Necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables
Jakob Runge
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Generic Neural Architecture Search via Regression
Yuhong Li · Cong Hao · Pan Li · Jinjun Xiong · Deming Chen
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Probabilistic Tensor Decomposition of Neural Population Spiking Activity
Hugo Soulat · Sepiedeh Keshavarzi · Troy Margrie · Maneesh Sahani
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Safe Reinforcement Learning with Natural Language Constraints
Tsung-Yen Yang · Michael Y Hu · Yinlam Chow · Peter J Ramadge · Karthik Narasimhan
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iFlow: Numerically Invertible Flows for Efficient Lossless Compression via a Uniform Coder
Shifeng Zhang · Ning Kang · Tom Ryder · Zhenguo Li
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On Linear Stability of SGD and Input-Smoothness of Neural Networks
Chao Ma · Lexing Ying
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SPANN: Highly-efficient Billion-scale Approximate Nearest Neighborhood Search
Qi Chen · Bing Zhao · Haidong Wang · Mingqin Li · Chuanjie Liu · Zhiyong Zheng · Mao Yang · Jingdong Wang
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Subgame solving without common knowledge
Brian Zhang · Tuomas Sandholm
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Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State
Mingqing Xiao · Qingyan Meng · Zongpeng Zhang · Yisen Wang · Zhouchen Lin
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Early-stopped neural networks are consistent
Ziwei Ji · Justin Li · Matus Telgarsky
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A single gradient step finds adversarial examples on random two-layers neural networks
Sebastien Bubeck · Yeshwanth Cherapanamjeri · Gauthier Gidel · Remi Tachet des Combes
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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 Sinz
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Private Non-smooth ERM and SCO in Subquadratic Steps
Janardhan Kulkarni · Yin Tat Lee · Daogao Liu
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Generalization Bounds For Meta-Learning: An Information-Theoretic Analysis
Qi CHEN · Changjian Shui · Mario Marchand
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Techniques for Symbol Grounding with SATNet
Sever Topan · David Rolnick · Xujie Si
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Combiner: Full Attention Transformer with Sparse Computation Cost
Hongyu Ren · Hanjun Dai · Zihang Dai · Mengjiao Yang · Jure Leskovec · Dale Schuurmans · Bo Dai
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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
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Intriguing Properties of Vision Transformers
Muhammad Muzammal Naseer · Kanchana Ranasinghe · Salman H Khan · Munawar Hayat · Fahad Shahbaz Khan · Ming-Hsuan Yang
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Look at What I’m Doing: Self-Supervised Spatial Grounding of Narrations in Instructional Videos
Reuben Tan · Bryan Plummer · Kate Saenko · Hailin Jin · Bryan Russell
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Hash Layers For Large Sparse Models
Stephen Roller · Sainbayar Sukhbaatar · arthur d szlam · Jason Weston
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Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms
Chi Jin · Qinghua Liu · Sobhan Miryoosefi
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Bias and variance of the Bayesian-mean decoder
Arthur Prat-Carrabin · Michael Woodford
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Neural optimal feedback control with local learning rules
Johannes Friedrich · Siavash Golkar · Shiva Farashahi · Alexander Genkin · Anirvan Sengupta · Dmitri Chklovskii
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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
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Improved Learning Rates of a Functional Lasso-type SVM with Sparse Multi-Kernel Representation
shaogao lv · Junhui Wang · Jiankun Liu · Yong Liu
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Neural Scene Flow Prior
Xueqian Li · Jhony Kaesemodel Pontes · Simon Lucey
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Mixture Proportion Estimation and PU Learning:A Modern Approach
Saurabh Garg · Yifan Wu · Alexander J Smola · Sivaraman Balakrishnan · Zachary Lipton
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On the Existence of The Adversarial Bayes Classifier
Pranjal Awasthi · Natalie Frank · Mehryar Mohri
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Sequential Algorithms for Testing Closeness of Distributions
Aadil Oufkir · Omar Fawzi · Nicolas Flammarion · Aurélien Garivier
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Deep Self-Dissimilarities as Powerful Visual Fingerprints
Idan Kligvasser · Tamar Shaham · Yuval Bahat · Tomer Michaeli
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Learning Interpretable Decision Rule Sets: A Submodular Optimization Approach
Fan Yang · Kai He · Linxiao Yang · Hongxia Du · Jingbang Yang · Bo Yang · Liang Sun
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Measuring Generalization with Optimal Transport
Ching-Yao Chuang · Youssef Mroueh · Kristjan Greenewald · Antonio Torralba · Stefanie Jegelka
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A$^2$-Net: Learning Attribute-Aware Hash Codes for Large-Scale Fine-Grained Image Retrieval
Xiu-Shen Wei · Yang Shen · Xuhao Sun · Han-Jia Ye · Jian Yang
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Tensor Normal Training for Deep Learning Models
Yi Ren · Donald Goldfarb
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Ultrahyperbolic Neural Networks
Marc Law
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Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning
Christoph Dann · Teodor Vanislavov Marinov · Mehryar Mohri · Julian Zimmert
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Vector-valued Distance and Gyrocalculus on the Space of Symmetric Positive Definite Matrices
Federico Lopez · Beatrice Pozzetti · Steve Trettel · Michael Strube · Anna Wienhard
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Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond
Maria-Florina Balcan · Siddharth Prasad · Tuomas Sandholm · Ellen Vitercik
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Embedding Principle of Loss Landscape of Deep Neural Networks
Yaoyu Zhang · Zhongwang Zhang · Tao Luo · Zhiqin J Xu
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Subgraph Federated Learning with Missing Neighbor Generation
Ke ZHANG · Carl Yang · Xiaoxiao Li · Lichao Sun · Siu Ming Yiu
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Neural Program Generation Modulo Static Analysis
Rohan Mukherjee · Yeming Wen · Dipak Chaudhari · Thomas Reps · Swarat Chaudhuri · Christopher Jermaine
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Proper Value Equivalence
Christopher Grimm · Andre Barreto · Greg Farquhar · David Silver · Satinder Singh
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Bootstrap Your Object Detector via Mixed Training
Mengde Xu · Zheng Zhang · Fangyun Wei · Yutong Lin · Yue Cao · Stephen Lin · Han Hu · Xiang Bai
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On the Representation of Solutions to Elliptic PDEs in Barron Spaces
Ziang Chen · Jianfeng Lu · Yulong Lu
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Decentralized Learning in Online Queuing Systems
Flore Sentenac · Etienne Boursier · Vianney Perchet
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Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning
Kai Wang · Sanket Shah · Haipeng Chen · Andrew Perrault · Finale Doshi-Velez · Milind Tambe
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Private learning implies quantum stability
Yihui Quek · Srinivasan Arunachalam · John A Smolin
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Tractable Regularization of Probabilistic Circuits
Anji Liu · Guy Van den Broeck
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Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning
Colin Wei · Sang Michael Xie · Tengyu Ma
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Instance-Dependent Partial Label Learning
Ning Xu · Congyu Qiao · Xin Geng · Min-Ling Zhang
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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
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Learning to delegate for large-scale vehicle routing
Sirui Li · Zhongxia Yan · Cathy Wu
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Width-based Lookaheads with Learnt Base Policies and Heuristics Over the Atari-2600 Benchmark
Stefan O'Toole · Nir Lipovetzky · Miquel Ramirez · Adrian Pearce
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On the Value of Infinite Gradients in Variational Autoencoder Models
Bin Dai · Li Wenliang · David P Wipf
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Uniform Concentration Bounds toward a Unified Framework for Robust Clustering
Debolina Paul · Saptarshi Chakraborty · Swagatam Das · Jason Xu
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Pruning Randomly Initialized Neural Networks with Iterative Randomization
Daiki Chijiwa · Shin'ya Yamaguchi · Yasutoshi Ida · Kenji Umakoshi · Tomohiro INOUE
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Reinforcement Learning in Newcomblike Environments
James Bell · Linda Linsefors · Caspar Oesterheld · Joar Skalse
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Variational Bayesian Optimistic Sampling
Brendan O'Donoghue · Tor Lattimore
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Coresets for Clustering with Missing Values
Vladimir braverman · Shaofeng Jiang · Robert Krauthgamer · Xuan Wu
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Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations
Ayush Sekhari · Christoph Dann · Mehryar Mohri · Yishay Mansour · Karthik Sridharan
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Mixability made efficient: Fast online multiclass logistic regression
Rémi Jézéquel · Pierre Gaillard · Alessandro Rudi
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PLUGIn: A simple algorithm for inverting generative models with recovery guarantees
Babhru Joshi · Xiaowei Li · Yaniv Plan · Ozgur Yilmaz
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Deep learning is adaptive to intrinsic dimensionality of model smoothness in anisotropic Besov space
Taiji Suzuki · Atsushi Nitanda
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Robust and Fully-Dynamic Coreset for Continuous-and-Bounded Learning (With Outliers) Problems
Zixiu Wang · Yiwen Guo · Hu Ding
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Robust Learning of Optimal Auctions
Wenshuo Guo · Michael Jordan · Emmanouil Zampetakis
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Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update
Michal Derezinski · Jonathan Lacotte · Mert Pilanci · Michael W Mahoney
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Collaborating with Humans without Human Data
DJ Strouse · Kevin McKee · Matt Botvinick · Edward Hughes · Richard Everett
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Refined Learning Bounds for Kernel and Approximate $k$-Means
Yong Liu
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Towards optimally abstaining from prediction with OOD test examples
Adam Kalai · Varun Kanade
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Coresets for Time Series Clustering
Lingxiao Huang · K Sudhir · Nisheeth Vishnoi
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Explaining Latent Representations with a Corpus of Examples
Jonathan Crabbe · Zhaozhi Qian · Fergus Imrie · Mihaela van der Schaar
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Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning
Gen Li · Laixi Shi · Yuxin Chen · Yuantao Gu · Yuejie Chi
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GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles
Octavian Ganea · Lagnajit Pattanaik · Connor Coley · Regina Barzilay · Klavs Jensen · William Green · Tommi Jaakkola
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How Well do Feature Visualizations Support Causal Understanding of CNN Activations?
Roland S. Zimmermann · Judy Borowski · Robert Geirhos · Matthias Bethge · Thomas Wallis · Wieland Brendel
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Towards a Unified Information-Theoretic Framework for Generalization
Mahdi Haghifam · Gintare Karolina Dziugaite · Shay Moran · Dan Roy
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DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks
Pál András Papp · Karolis Martinkus · Lukas Faber · Roger Wattenhofer
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Aligned Structured Sparsity Learning for Efficient Image Super-Resolution
Yulun Zhang · Huan Wang · Can Qin · Yun Fu
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Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions
Bruno Loureiro · Gabriele Sicuro · Cedric Gerbelot · Alessandro Pacco · Florent Krzakala · Lenka Zdeborová
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Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization
Yusuke Iwasawa · Yutaka Matsuo
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Bayesian Bellman Operators
Mattie Fellows · Kristian Hartikainen · Shimon Whiteson
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Bayesian decision-making under misspecified priors with applications to meta-learning
Max Simchowitz · Christopher Tosh · Akshay Krishnamurthy · Daniel Hsu · Thodoris Lykouris · Miro Dudik · Robert E Schapire
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Diffusion Models Beat GANs on Image Synthesis
Prafulla Dhariwal · Alexander Nichol
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Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning
Hanzhe Hu · Fangyun Wei · Han Hu · Qiwei Ye · Jinshi Cui · Liwei Wang
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Neural Algorithmic Reasoners are Implicit Planners
Andreea-Ioana Deac · Petar Veličković · Ognjen Milinkovic · Pierre-Luc Bacon · Jian Tang · Mladen Nikolic
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TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation
Haoang Chi · Feng Liu · Wenjing Yang · Long Lan · Tongliang Liu · Bo Han · William Cheung · James Kwok
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Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space
Sandesh Ghimire · Aria Masoomi · Jennifer Dy
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Uncertain Decisions Facilitate Better Preference Learning
Cassidy Laidlaw · Stuart Russell
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Maximum Likelihood Training of Score-Based Diffusion Models
Yang Song · Conor Durkan · Iain Murray · Stefano Ermon
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List-Decodable Mean Estimation in Nearly-PCA Time
Ilias Diakonikolas · Daniel Kane · Daniel Kongsgaard · Jerry Li · Kevin Tian
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What’s a good imputation to predict with missing values?
Marine Le Morvan · Julie Josse · Erwan Scornet · Gael Varoquaux
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Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms
Alexander Camuto · George Deligiannidis · Murat Erdogdu · Mert Gurbuzbalaban · Umut Simsekli · Lingjiong Zhu
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Precise characterization of the prior predictive distribution of deep ReLU networks
Lorenzo Noci · Gregor Bachmann · Kevin Roth · Sebastian Nowozin · Thomas Hofmann
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Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems
Suhas S Kowshik · Dheeraj Nagaraj · Prateek Jain · Praneeth Netrapalli
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Robust Predictable Control
Ben Eysenbach · Russ Salakhutdinov · Sergey Levine
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A Central Limit Theorem for Differentially Private Query Answering
Jinshuo Dong · Weijie Su · Linjun Zhang
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Near-Optimal Lower Bounds For Convex Optimization For All Orders of Smoothness
Ankit Garg · Robin Kothari · Praneeth Netrapalli · Suhail Sherif
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Flexible Option Learning
Martin Klissarov · Doina Precup
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Understanding the Under-Coverage Bias in Uncertainty Estimation
Yu Bai · Song Mei · Huan Wang · Caiming Xiong
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Instance-Conditioned GAN
Arantxa Casanova · Marlene Careil · Jakob Verbeek · Michal Drozdzal · Adriana Romero Soriano
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Fair Exploration via Axiomatic Bargaining
Jackie Baek · Vivek Farias
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Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGD
Rémi Bardenet · Subhroshekhar Ghosh · Meixia LIN
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FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout
Samuel Horváth · Stefanos Laskaridis · Mario Almeida · Ilias Leontiadis · Stylianos Venieris · Nicholas Lane
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Towards Gradient-based Bilevel Optimization with Non-convex Followers and Beyond
Risheng Liu · Yaohua Liu · Shangzhi Zeng · Jin Zhang
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Probabilistic Attention for Interactive Segmentation
Prasad Gabbur · Manjot Bilkhu · Javier Movellan
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Two steps to risk sensitivity
Christopher Gagne · Peter Dayan
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Multimodal and Multilingual Embeddings for Large-Scale Speech Mining
Paul-Ambroise Duquenne · Hongyu Gong · Holger Schwenk
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Slice Sampling Reparameterization Gradients
David M Zoltowski · Diana Cai · Ryan Adams
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Focal Attention for Long-Range Interactions in Vision Transformers
Jianwei Yang · Chunyuan Li · Pengchuan Zhang · Xiyang Dai · Bin Xiao · Lu Yuan · Jianfeng Gao
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Learning Disentangled Behavior Embeddings
Changhao Shi · Sivan Schwartz · Shahar Levy · Shay Achvat · Maisan Abboud · Amir Ghanayim · Jackie Schiller · Gal Mishne
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Continuous vs. Discrete Optimization of Deep Neural Networks
Omer Elkabetz · Nadav Cohen
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Statistical Query Lower Bounds for List-Decodable Linear Regression
Ilias Diakonikolas · Daniel Kane · Ankit Pensia · Thanasis Pittas · Alistair Stewart
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Sequence-to-Sequence Learning with Latent Neural Grammars
Yoon Kim
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RL for Latent MDPs: Regret Guarantees and a Lower Bound
Jeongyeol Kwon · Yonathan Efroni · Constantine Caramanis · Shie Mannor
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Revisiting ResNets: Improved Training and Scaling Strategies
Irwan Bello · William Fedus · Xianzhi Du · Ekin Dogus Cubuk · Aravind Srinivas · Tsung-Yi Lin · Jonathon Shlens · Barret Zoph
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Per-Pixel Classification is Not All You Need for Semantic Segmentation
Bowen Cheng · Alex Schwing · Alexander Kirillov
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Littlestone Classes are Privately Online Learnable
Noah Golowich · Roi Livni
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Regulating algorithmic filtering on social media
Sarah Cen · Devavrat Shah
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Parametric Complexity Bounds for Approximating PDEs with Neural Networks
Tanya Marwah · Zachary Lipton · Andrej Risteski
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Property-Aware Relation Networks for Few-Shot Molecular Property Prediction
Yaqing Wang · Abulikemu Abuduweili · Quanming Yao · Dejing Dou
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Light Field Networks: Neural Scene Representations with Single-Evaluation Rendering
Vincent Sitzmann · Semon Rezchikov · Bill Freeman · Josh Tenenbaum · Fredo Durand
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Learning Equilibria in Matching Markets from Bandit Feedback
Meena Jagadeesan · Alexander Wei · Yixin Wang · Michael Jordan · Jacob Steinhardt
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Random Shuffling Beats SGD Only After Many Epochs on Ill-Conditioned Problems
Itay Safran · Ohad Shamir
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Logarithmic Regret in Feature-based Dynamic Pricing
Jianyu Xu · Yu-Xiang Wang