[edit]

Accepted Papers

Notable papers

• Who Should Predict? Exact Algorithms For Learning to Defer to Humans
  Mozannar, Hussein; Lang, Hunter; Wei, Dennis; Sattigeri, Prasanna; Das, Subhro; Sontag, David


• Implications of sparsity and high triangle density for graph representation learning
  Sansford, Hannah J; Modell, Alexander; Whiteley, Nick; Rubin-Delanchy, Patrick


• Fitting low-rank models on egocentrically sampled partial networks
  Chan, Ga Ming Angus; Li, Tianxi


• The Power of Recursion in Graph Neural Networks for Counting Substructures
  Tahmasebi, Behrooz; Lim, Derek; Jegelka, Stefanie


• Rethinking Initialization of the Sinkhorn Algorithm
  Thornton, James; Cuturi, marco


• Using Sliced Mutual Information to Study Memorization and Generalization in Deep Neural Networks
  Wongso, Shelvia; Ghosh, Rohan; Motani, Mehul


• Noisy Low-rank Matrix Optimization: Geometry of Local Minima and Convergence Rate
  Ma, Ziye; Sojoudi, Somayeh


• Federated Learning under Distributed Concept Drift
  Jothimurugesan, Ellango; Hsieh, Kevin; Wang, Jianyu; Joshi, Gauri; Gibbons, Phillip B


• Error Estimation for Random Fourier Features
  Yao, Junwen; Erichson, Benjamin; Lopes, Miles E


• Implicit Graphon Neural Representation
  Xia, Xinyue; Mishne, Gal; Wang, Yusu


• A Tale of Sampling and Estimation in Discounted Reinforcement Learning
  Metelli, Alberto Maria; Mutti, Mirco; Restelli, Marcello


• Fix-A-Step: Semi-supervised Learning From Uncurated Unlabeled Data
  Huang, Zhe; Sidhom, Mary-Joy; Wessler, Benjamin; Hughes, Michael C


• BaCaDI: Bayesian Causal Discovery with Unknown Interventions
  Hägele, Alexander; Rothfuss, Jonas; Lorch, Lars; Somnath, Vignesh Ram; Schölkopf, Bernhard; Krause, Andreas


• Mode-Seeking Divergences: Theory and Applications to GANs
  Li, Cheuk Ting; Farnia, Farzan


• The Schrödinger Bridge between Gaussian Measures has a Closed Form
  Bunne, Charlotte; Hsieh, Ya-Ping; Cuturi, marco; Krause, Andreas


• Huber-robust confidence sequences
  Wang, Hongjian; Ramdas, Aaditya


• Blessing of Class Diversity in Pre-training
  Zhao, Yulai; Chen, Jianshu; Du, Simon


• Hedging against Complexity: Distributionally Robust Optimization with Parametric Approximation
  Iyengar, Garud; Lam, Henry; Wang, Tianyu


• Scalable Bicriteria Algorithms for Non-Monotone Submodular Cover
  Crawford, Victoria


• Scalable particle-based alternatives to EM
  Kuntz Nussio, Juan; Lim, Jen Ning; Johansen, Adam M.


• Do Bayesian Neural Networks Need to be Fully Stochastic?
  Sharma, Mrinank; Farquhar, Sebastian; Nalisnick, Eric; Rainforth, Tom


• Distance-to-Set Priors and Constrained Bayesian Inference
  Presman, Rick; Xu, Jason Q


• An Efficient and Continuous Voronoi Density Estimator
  Marchetti, Giovanni Luca; Polianskii, Vladislav; Varava, Anastasiia; Pokorny, Florian T.; Kragic, Danica


• Multilevel Bayesian Quadrature
  Li, Kaiyu; Giles, Daniel; Karvonen, Toni; Guillas, Serge; Briol, Francois-Xavier


• Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation
  Moss, Henry B; Ober, Sebastian W; Picheny, Victor


• Discovering Many Diverse Solutions with Bayesian Optimization
  Maus, Natalie; Wu, Kaiwen; Eriksson, David; Gardner, Jacob


• Indeterminacy in Generative Models: Characterization and Strong Identifiability
  Xi, Quanhan; Bloem-Reddy, Benjamin


• Robust Sequential Testing and Effect Estimation in Stratified Count Data
  Turner, Rosanne; Grunwald, Peter


• Data Banzhaf: A Robust Data Valuation Framework for Machine Learning
  Wang, Tianhao; Jia, Ruoxi


• Combating label-leaking explanations
  Jethani, Neil; Saporta, Adriel; Ranganath, Rajesh


• Generalized PTR: User-Friendly Recipes for Data-Adaptive Algorithms with Differential Privacy
  Redberg, Rachel; Zhu, Yuqing; Wang, Yu-Xiang


• Origins of Low-Dimensional Adversarial Perturbations
  Dohmatob, Elvis; Guo, Chuan; Goibert, Morgane

All Accepted Papers

• Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation
  Sakaue, Shinsaku; Oki, Taihei


• Meta-Uncertainty in Bayesian Model Comparison
  Schmitt, Marvin; Radev, Stefan T.; Bürkner, Paul-Christian


• PAC Learning of Halfspaces with Malicious Noise in Nearly Linear Time
  Shen, Jie


• Entropic Risk Optimization in Discounted MDPs
  Hau, Jia Lin; Petrik, Marek; Ghavamzadeh, Mohammad


• Acceleration of Frank-Wolfe Algorithms with Open Loop Step-Sizes
  Wirth, Elias S; Kerdreux, Thomas; Pokutta, Sebastian


• An Online and Unified Algorithm for Projection Matrix Vector Multiplication with Application to Empirical Risk Minimization
  Qin, Lianke; Song, Zhao; Zhang, Lichen; Zhuo, Danyang


• Leveraging Instance Features for Label Aggregation in Programmatic Weak Supervision
  Zhang, Jieyu; Song, Linxin; Ratner, Alex


• Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods
  Beznosikov, Aleksandr; Gorbunov, Eduard; Berard, Hugo; Loizou, Nicolas


• Scalable marked point processes for exchangeable and non-exchangeable event sequences
  Panos, Aristeidis; Kosmidis, Ioannis; Dellaportas, Petros


• Bayesian Variable Selection in a Million Dimensions
  Jankowiak, Martin


• Blessing of Class Diversity in Pre-training
  Zhao, Yulai; Chen, Jianshu; Du, Simon


• Barlow Graph Auto-Encoder for Unsupervised Network Embedding
  Khan, RayyanAhmad; Kleinsteuber, Martin


• Gradient-Informed Neural Network Statistical Robustness Estimation
  TIT, Karim; Furon, Teddy; Rousset, Mathias


• Online Defense Strategies for Reinforcement Learning Against Adaptive Reward Poisoning
  Nika, Andi; Singla, Adish; Radanovic, Goran


• A Case of Exponential Convergence Rates for SVM
  Cabannnes, Vivien A; Vigogna, Stefano


• Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning
  Xu, Ruitu; Min, Yifei; Wang, Tianhao; Jordan, Michael; Wang, Zhaoran; Yang, Zhuoran


• Adaptive Cholesky Gaussian Processes
  Bartels, Simon; Stensbo-Smidt, Kristoffer; Moreno-Munoz, Pablo; Boomsma, Wouter Krogh; Frellsen, Jes; Hauberg, Soren


• Sample Complexity of Kernel-Based Q-Learning
  Yeh, Sing-Yuan; Chang, Fu-Chieh; Yueh, Chang-Wei; Wu, Pei-Yuan; Bernacchia, Alberto; Vakili, Sattar


• A principled framework for the design and analysis of token algorithms
  Hendrikx, Hadrien


• Learning k-qubit Quantum Operators via Pauli Decomposition
  Heidari, Mohsen; Szpankowski, Wojciech


• Semi-Verified PAC Learning from the Crowd
  Zeng, Shiwei; Shen, Jie


• On the Capacity Limits of Privileged ERM
  Sharoni, Michal; Sabato, Sivan


• USIM Gate: Novel Attention-based UpSampling Interpolation Method for Segmenting Precise Boundaries of Target Objects
  Lee, Kyungsu; Lee, Haeyun; Hwang, Jae Youn


• Bayesian Structure Scores for Probabilistic Circuits
  Yang, Yang; Gala, Gennaro; Peharz, Robert


• Langevin Diffusion Variational Inference
  Geffner, Tomas; Domke, Justin


• Overcoming Prior Misspecification in Online Learning to Rank
  Azizi, MohammadJavad; Meshi, Ofer; Zoghi, Masrour; Karimzadehgan, Maryam


• Catalyst Acceleration of Error Compensated Methods Leads to Better Communication Complexity
  Qian, Xun; Dong, Hanze; Zhang, Tong; Richtarik, Peter


• Kernel Conditional Moment Constraints for Confounding Robust Inference
  Ishikawa, Kei; He, Niao


• Meta-learning for Robust Unsupervised Anomaly Detection
  Kumagai, Atsutoshi; Iwata, Tomoharu; Takahashi, Hiroshi; Fujiwara, Yasuhiro


• Learning in RKHM: a C*-algebraic twist for kernel machines
  Hashimoto, Yuka; Ikeda, Masahiro; Kadri, Hachem


• From Shapley Values to Generalized Additive Models and back
  Bordt, Sebastian; von Luxburg, Ulrike


• Estimating Conditional Average Treatment Effects with Missing Treatment Information
  Kuzmanovic, Milan; Hatt, Tobias; Feuerriegel, Stefan


• Global Convergence of Over-parameterized Deep Equilibrium Models
  Ling, Zenan; Xie, Xingyu; Wang, Qiuhao; Zhang, Zongpeng; Lin, Zhouchen


• A Tale of Two Efficient Value Iteration Algorithms for Solving Linear MDPs with Large Action Space
  Xu, Zhaozhuo; Song, Zhao; Shrivastava, Anshumali


• Adversarial De-confounding in Individualised Treatment Effects Estimation
  Chauhan, Vinod K; Molaei, Soheila; Hoque Tania , Marzia ; Thakur, Anshul; Zhu, Tingting; Clifton, David A


• Fast Distributed k-Means with a Small Number of Rounds
  Hess, Tom; Visbord, Ron; Sabato, Sivan


• A New Causal Decomposition Paradigm towards Health Equity
  Sun, Xinwei; Zheng, Xiangyu; Weinstein, Jim


• Matching Map Recovery with an Unknown Number of Outliers
  Minasyan, Arshak; Galstyan, Tigran; Hunanyan, Sona; Dalalyan, Arnak


• Characterizing Internal Evasion Attacks in Federated Learning
  Kim, Taejin; Singh, Shubhranshu ; Madaan, Nikhil; Joe-Wong, Carlee


• Optimal and Private Learning from Human Response Data
  Nguyen, Duc; Zhang, Anderson Ye


• Bayesian Optimization with Conformal Coverage Guarantees
  Stanton, Samuel; Maddox, Wesley; Wilson, Andrew Gordon Gordon


• Alternating Projected SGD for Equality-constrained Bilevel Optimization
  Xiao, Quan; Shen, Han ; Yin, Wotao; Chen, Tianyi


• Improved Robust Algorithms for Learning with Discriminative Feature Feedback
  Sabato, Sivan


• Weisfeiler and Leman go Hyperbolic: Learning Distance Preserving Node Representations
  Nikolentzos, Giannis; Chatzianastasis, Michail; Vazirgiannis, Michalis


• Can 5th Generation Local Training Methods Support Client Sampling? Yes!
  Grudzień, Michał; Malinovsky, Grigory; Richtarik, Peter


• qEUBO: A Decision-Theoretic Acquisition Function for Preferential Bayesian Optimization
  Astudillo, Raul; Lin, Zhiyuan Jerry; Bakshy, Eytan; Frazier, Peter


• Bayesian Hierarchical Models for Counterfactual Estimation
  Raman, Natraj; Magazzeni, Daniele; Shah, Sameena


• Sequential Gradient Descent and Newton's Method for Change-Point Analysis
  Zhang, Xianyang; Dawn, Trisha


• Towards Scalable and Robust Structured Bandits: A Meta-Learning Framework
  Wan, Runzhe; Ge, Lin; Song, Rui


• Compress Then Test: Powerful Kernel Testing in Near-linear Time
  Domingo-Enrich, Carles; Dwivedi, Raaz; Mackey, Lester


• Select and Optimize Learning to Solve Large-Scale Traveling Salesman Problem
  Cheng, Hanni; Zheng, Haosi; Cong, Ya; Jiang, Weihao; Pu, Shiliang


• Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity
  Allouah, Youssef; Farhadkhani, Sadegh; Guerraoui, Rachid; Gupta, Nirupam; Pinot, Rafael; Stephan, John


• Testing of Horn Samplers
  BANERJEE, ANSUMAN; Chakraborty, Shayak; Chakraborty, Sourav; Meel, Kuldeep S; Sarkar, Uddalok; Sen, Sayantan


• Coordinate Ascent for Off-Policy RL with Global Convergence Guarantees
  Su, Hsin-En; Chen, Yen-Ju; Hsieh, Ping-Chun; Liu, Xi


• Positional Encoder Graph Neural Networks for Geographic Data
  Klemmer, Konstantin; Safir, Nathan S; Neill, Daniel B


• Coarse-Grained Smoothness for Reinforcement Learning in Metric Spaces
  Gottesman, Omer; Asadi, Kavosh; Allen, Cameron S; Lobel, Samuel; Konidaris, George; Littman, Michael L.


• BaCaDI: Bayesian Causal Discovery with Unknown Interventions
  Hägele, Alexander; Rothfuss, Jonas; Lorch, Lars; Somnath, Vignesh Ram; Schölkopf, Bernhard; Krause, Andreas


• Statistical Analysis of Karcher Means for Random Restricted PSD Matrices
  Chen, Hengchao; Li, Xiang; Sun, Qiang


• Differentially Private Synthetic Control
  Rho, Saeyoung; Cummings, Rachel; Misra, Vishal


• Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes
  Jimenez, Felix; Katzfuss, Matthias


• A Randomly Pruned Neural Network can be Equivalent to the Unpruned Network under the NTK Regime
  Yang, Hongru; Wang, Zhangyang


• Riemannian accelerated gradient methods via extrapolation
  Han, Andi; Mishra, Bamdev; Jawanpuria, Pratik; Gao, Junbin


• Flexible risk design using bi-directional dispersion
  Holland, Matthew J


• Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles
  Kim, Jung-hun; Yun, Se-Young; Jeong, Minchan; Nam, Junhyun; Shin, Jinwoo; Combes, Richard


• Deep equilibrium models as estimators for continuous latent variables
  Tsuchida, Russell; Ong, Cheng Soon


• Refined Convergence and Topology Learning for Decentralized SGD with Heterogeneous Data
  Le Bars, Batiste; Bellet, Aurélien; Tommasi, Marc; Lavoie, Erick; Kermarrec, Anne-Marie


• A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces
  Le Lan, Charline; Greaves, Joshua; Farebrother, Jesse; Rowland, Mark; Pedregosa, Fabian; Agarwal, Rishabh; G. Bellemare, Marc


• A Constant-Factor Approximation Algorithm for Reconciliation $k$-Median
  Gionis, Aristides; Khodamoradi, Kamyar; Ordozgoiti, Bruno; Riegel, Benedikt; Spoerhase, Joachim


• Neural Laplace Control for Continuous-time Delayed Systems
  Holt, Samuel I; Hüyük, Alihan; Qian, Zhaozhi; Sun, Hao; van der Schaar, Mihaela


• Discovering Many Diverse Solutions with Bayesian Optimization
  Maus, Natalie; Wu, Kaiwen; Eriksson, David; Gardner, Jacob


• BlitzMask: Real-Time Instance Segmentation Approach for Mobile Devices
  Bulygin, Vitalii; Mykheievskyi, Dmytro; Kuchynskyi, Kyrylo


• Exact Gradient Computation for Spiking Neural Networks
  Lee, Jane H; Haghighatshoar, Saeid; Karbasi, Amin


• Uni6Dv2: Noise Elimination for 6D Pose Estimation
  Sun, Mingshan; Zheng, Ye; Bao, Tianpeng; Chen, Jianqiu; Jin, Guoqiang; Wu, Liwei; Zhao, Rui; Jiang, Xiaoke


• Multilevel Bayesian Quadrature
  Li, Kaiyu; Giles, Daniel; Karvonen, Toni; Guillas, Serge; Briol, Francois-Xavier


• Direct Inference of Effect of Treatment (DIET) for a Cookieless World
  Shankar, Shiv; Sinha, Ritwik; Mitra, Saayan; Sinha, Moumita; Fiterau, Madalina


• The Ordered Matrix Dirichlet for Modeling Ordinal Dynamics
  Stoehr, Niklas; Radford, Benjamin J; Cotterell, Ryan; Schein, Aaron J


• Energy-Based Processes for Functional Data
  Lim, Jen Ning; Vollmer, Sebastian; Wolf, Lorenz L; Duncan, Andrew


• Frequentist Uncertainty Quantification in Semi-Structured Neural Networks
  Dorigatti, Emilio; Schubert, Benjamin; Bischl, Bernd; Ruegamer, David


• NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge
  Sun, Xiangyu; Schulte, Oliver; Liu, Guiliang; Poupart, Pascal


• One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement Learning
  Cisneros-Velarde, Pedro; Lyu, Boxiang; Koyejo, Sanmi; Kolar, Mladen


• Variational Inference for Neyman-Scott Processes
  Hong, Chengkuan; Shelton, Christian


• Graph Alignment Kernels using Weisfeiler and Leman Hierarchies
  Nikolentzos, Giannis; Vazirgiannis, Michalis


• Geometric Random Walk Graph Neural Networks via Implicit Layers
  Nikolentzos, Giannis; Vazirgiannis, Michalis


• Model-Free Sequential Testing for Conditional Independence via Testing by Betting
  Shaer, Shalev; Maman, Gal; Romano, Yaniv


• Mixed-Effect Thompson Sampling
  Aouali, Imad; Kveton, Branislav; Katariya, Sumeet


• Mixed Linear Regression via Approximate Message Passing
  Tan, Nelvin; Venkataramanan, Ramji


• EEGNN: Edge Enhanced Graph Neural Networks
  Liu, Yirui; Qiao, Xinghao; Wang, Liying; Lam, Jessica


• Estimating Total Correlation with Mutual Information Estimators
  Bai, Ke; Cheng, Pengyu; Hao, Weituo; Henao, Ricardo; Carin, Larry


• Vector Optimization with Stochastic Bandit Feedback
  Ararat, Cagin; Tekin, Cem


• Knowledge Acquisition for Human-In-The-Loop Image Captioning
  Zheng, Ervine; Yu, Qi; Li, Rui; Shi, Pengcheng; Haake, Anne


• A Statistical Analysis of Polyak-Ruppert-Averaged Q-Learning
  Li, Xiang; Yang, Wenhao; Liang, Jiadong; Zhang, Zhihua; Jordan, Michael


• Linear Convergence of Gradient Descent For Overparametrized Finite Width Two-Layer Linear Networks With General Initialization
  Xu, Ziqing; Min, Hancheng; Tarmoun, Salma; Mallada, Enrique; Vidal, Rene


• “Plus/minus the learning rate”: Easy and Scalable Statistical Inference with SGD
  Chee, Jerry; Kim, Hwanwoo; Toulis, Panos


• Distance-to-Set Priors and Constrained Bayesian Inference
  Presman, Rick; Xu, Jason Q


• Fast Computation of Branching Process Transition Probabilities via ADMM
  AWASTHI, ACHAL; Xu, Jason Q


• Error Estimation for Random Fourier Features
  Yao, Junwen; Erichson, Benjamin; Lopes, Miles E


• AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization
  Huang, Feihu; Wu, Xidong; Hu, Zhengmian


• Classification of Adolescents' Risky Behavior in Instant Messaging Conversations
  Plhák, Jaromír; Sotolář, Ondřej; Lebedíková, Michaela; Šmahel, David


• Robust Linear Regression for General Feature Distribution
  Norman, Tom; Levy, Kfir; Weinberger, Nir; Levy, Kfir Yehuda; Weinberger, Nir


• Fair learning with Wasserstein barycenters for non-decomposable performance measures
  Gaucher, Solenne; Schreuder, Nicolas; Chzhen, Evgenii


• Deep Neural Networks with Efficient Guaranteed Invariances
  Rath, Matthias; Condurache, Alexandru


• Fast Block Coordinate Descent for Non-Convex Group Regularizations
  Ida, Yasutoshi; Kanai, Sekitoshi; Kumagai, Atsutoshi


• AUC-based Selective Classification
  Pugnana, Andrea; Ruggieri, Salvatore


• Nonparametric Indirect Active Learning
  Singh, Shashank


• Resolving the Approximability of Offline and Online Non-monotone DR-Submodular Maximization over General Convex Sets
  Mualem, Loay Raed; Feldman, Moran


• \{PF\}$^2$ES: Parallel Feasible Pareto Frontier Entropy Search for Multi-Objective Bayesian Optimization
  Qing, Jixiang; Moss, Henry B; Dhaene, Tom; Couckuyt, Ivo


• Learning Constrained Structured Spaces with Application to Multi-Graph Matching
  Cohen Indelman , Hedda; Hazan, Tamir


• On the Strategyproofness of the Geometric Median
  El-Mhamdi, El-Mahdi; Farhadkhani, Sadegh; Guerraoui, Rachid; Hoang, Lê-Nguyên


• Covariate-informed Representation Learning to Prevent Posterior Collapse of iVAE
  Kim, Young-geun; Liu, Ying; Wei, Xue-Xin


• EGG-GAE: scalable graph neural networks for tabular data imputation
  Telyatnikov, Lev; Scardapane, Simone


• Group Distributionally Robust Reinforcement Learning with Hierarchical Latent Variables
  Xu, Mengdi; Huang, Peide; Niu, Yaru; Kumar, Visak; Qiu, Jielin; Fang, Chao; Lee, Kuan-Hui; Qi, Xuewei ; Lam, Henry; Li, Bo; ZHAO, DING


• Weather2K: A Multivariate Spatio-Temporal Benchmark Dataset for Meteorological Forecasting Based on Real-Time Observation Data from Ground Weather Stations
  Zhu, Xun; Xiong, Yutong; Wu, Ming; Nie, Gaozhen; Zhang, Bin; Yang, Ziheng


• Improved Rate of First Order Algorithms for Entropic Optimal Transport
  Luo, Yiling; Xie, Yiling; Huo, Xiaoming


• Conformal Off-Policy Prediction
  zhang, yingying; Shi, Chengchun; Luo, Shikai


• Sparse Spectral Bayesian Permanental.Process with Generalized Kernel
  Sellier, Jeremy; Dellaportas, Petros


• Adversarial Noises Are Linearly Separable for （Nearly） Random Neural Networks
  Zhang, Huishuai; Yu, Da; Lu, Yiping; He, Di


• Nearly Optimal Latent State Decoding in Block MDPs
  Jedra, Yassir; Lee, Junghyun; Proutiere, Alexandre; Yun, Se-Young


• On the Limitations of the Elo, Real-World Games are Transitive, not Additive
  Bertrand, Quentin; Czarnecki, Wojciech M; Gidel, Gauthier


• Agnostic PAC Learning of k-Juntas Using L2-Polynomial Regression
  Heidari, Mohsen; Szpankowski, Wojciech


• Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group
  Wang, Zhenbang; Ben-David, Emanuel; Slawski, Martin


• Simulation-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms or Posterior Estimators for Inverse Problems
  Masserano, Luca; Dorigo, Tommaso; Izbicki, Rafael; Kuusela, Mikael; Lee, Ann


• Analysis of Catastrophic Forgetting for Random Orthogonal Transformation Tasks in the Overparameterized Regime
  Goldfarb, Daniel; Hand, Paul


• Clustering above Exponential Families with Tempered Exponential Measures
  Amid, Ehsan; Nock, Richard; Warmuth, Manfred K.


• Mind the (optimality) Gap: A Gap-Aware Learning Rate Scheduler for Adversarial Nets
  Hazimeh, Hussein; Ponomareva, Natalia


• Learning Physics-Informed Neural Networks without Stacked Back-propagation
  He, Di; Li, Shanda; Shi, Wenlei; Gao, Xiaotian; Zhang, Jia; Bian, Jiang; Wang, Liwei; Liu, Tie-Yan


• An Optimization-based Algorithm for Non-stationary Kernel Bandits without Prior Knowledge
  Hong, Kihyuk; Li, Yuhang; Tewari, Ambuj


• Multi-armed Bandit Experimental Design: Online Decision-making and Adaptive Inference
  Simchi-Levi, David; Wang, Chonghuan


• Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual Bandits
  Kim, Wonyoung; Paik, Myunghee Cho; Oh, Min-hwan


• Noisy Low-rank Matrix Optimization: Geometry of Local Minima and Convergence Rate
  Ma, Ziye; Sojoudi, Somayeh


• Byzantine-Robust Federated Learning with Optimal Statistical Rates
  Zhu, Banghua; Wang, Lun; Pang, Qi; Wang, Shuai; Jiao, Jiantao; Song, Dawn; Jordan, Michael


• An Unpooling Layer for Graph Generation
  Guo, Yinglong; Zou, Dongmian; Lerman, Gilad


• Online Learning for Traffic Routing under Unknown Preferences
  Jalota, Devansh; Gopalakrishnan, Karthik; Azizan, Navid; Johari, Ramesh ; Pavone, Marco


• Byzantine-Robust Online and Offline Distributed Reinforcement Learning
  Chen, Yiding; Zhang, Xuezhou; Zhang, Kaiqing; Wang, Mengdi; Zhu, Xiaojin


• No-Regret Learning in Two-Echelon Supply Chain with Unknown Demand Distribution
  Zhang, Mengxiao; Chen, Shi; Luo, Haipeng; Wang, Yingfei


• Mode Constrained Model-Based Reinforcement Learning via Gaussian Processes
  Scannell, Aidan; Ek, Carl Henrik; Richards, Arthur


• Generative Oversampling for Imbalanced Data via Majority-Guided VAE
  Ai, Qingzhong; Wang, Pengyun; He, Lirong; Wen, liangjian; Pan, Lujia; Xu, Zenglin


• The Lie-Group Bayesian Learning Rule
  Kiral, Eren Mehmet; Moellenhoff, Thomas; Emtiyaz, Khan Mohammad


• Singular Value Representation: A New Graph Perspective On Neural Networks
  Berkouk, Nicolas; Meller, Dan


• A Finite Sample Complexity Bound for Distributionally Robust Q-learning
  Wang, Shengbo; Si, Nian; Blanchet, Jose; Zhou, Zhengyuan


• Connectivity-contrastive learning: Combining causal discovery and representation learning for multimodal data
  Morioka, Hiroshi; Hyvarinen, Aapo


• A Bregman Divergence View on the Difference-of-Convex Algorithm
  Faust, Oisin; Fawzi, Hamza; Saunderson, James


• Minority Oversampling for Imbalanced Data via Class-Preserving Regularized Auto-Encoders
  Mondal, Arnab K; Singhal, Lakshya; Tiwary, Piyush; Singla, Parag; A P, Prathosh


• T-Phenotype: Discovering Phenotypes of Predictive Temporal Patterns in Disease Progression
  Qin, Yuchao; van der Schaar, Mihaela; Lee, Changhee


• Membership Inference Attacks against Synthetic Data through Overfitting Detection
  van Breugel, Boris; Sun, Hao; Qian, Zhaozhi; van der Schaar, Mihaela


• Online Learning for Non-monotone DR-Submodular Maximization: From Full Information to Bandit Feedback
  Zhang, Qixin; Deng, Zengde; Chen, Zaiyi; Zhou, Kuangqi; Hu, Haoyuan; Yang, Yu


• Robust Variational Autoencoding with Wasserstein Penalty for Novelty Detection
  Lai, Chieh-Hsin; Zou, Dongmian; Lerman, Gilad


• To Impute or not to Impute? Missing Data in Treatment Effect Estimation
  Berrevoets, Jeroen; Imrie, Fergus; Kyono, Trent M; Jordon, James; van der Schaar, Mihaela


• No-regret Sample-efficient Bayesian Optimization for Finding Nash Equilibria with Unknown Utilities
  Tay, Sebastian Shenghong; Nguyen, Quoc Phong; Foo, Chuan Sheng; Low, Bryan Kian Hsiang


• Noise-Aware Statistical Inference with Differentially Private Synthetic Data
  Räisä, Ossi; Jälkö, Joonas; Kaski, Samuel; Honkela, Antti


• ASkewSGD : An Annealed interval-constrained Optimisation method to train Quantized Neural Networks
  Leconte, Louis; Schechtman, Sholom; Moulines, Eric


• Transport Elliptical Slice Sampling
  Cabezas Gonzalez, Alberto ; Nemeth, Christopher


• Towards Balanced Representation Learning for Credit Policy Evaluation
  Huang, Yiyan; Leung, Cheuk Hang; Ma, Shumin; Yuan, Zhiri; Wu, Qi; WANG, SIYI; Wang, Dongdong; Huang, Zhixiang


• Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition
  Sun, Lukang; Karagulyan, Avetik ; Richtarik, Peter


• MARS: Masked Automatic Ranks Selection in Tensor Decompositions
  Kodryan, Maxim; Kropotov, Dmitry; Vetrov, Dmitry P


• Learning from Multiple Sources for Data-to-Text and Text-to-Data
  Duong, Song; Lumbreras, Alberto; Gartrell, Mike; Gallinari, Patrick


• Sparse Bayesian optimization
  Liu, Sulin; Feng, Qing; Eriksson, David; Letham, Benjamin; Bakshy, Eytan


• On the bias of K-fold cross validation with stable learners
  Aghbalou, Anass; Sabourin, Anne; Portier, François


• Bayesian Convolutional Deep Sets with Task-Dependent Stationary Prior
  Jung, Yohan; Park, Jinkyoo


• Sample Efficiency of Data Augmentation Consistency Regularization
  Yang, Shuo; Dong, Yijun; Ward, Rachel; Dhillon, Inderjit S.; Sanghavi, Sujay; Lei, Qi


• ANACONDA: Improved Dynamic Regret Algorithm for Adaptive Non-Stationary Dueling Bandits
  Kleine Buening, Thomas; Saha, Aadirupa


• Deep Joint Source Channel Coding with Iterative Source Error Correction
  Lee, Changwoo; Hu, Xiao; Kim, Hun Seok


• On-Demand Communication for Asynchronous Multi-Agent Bandits
  Chen, Yu-Zhen Janice; Yang, Lin; Wang, Xuchuang; Liu, Xutong; Hajiesmaili, Mohammad; Lui, John C. S.; Towsley, Don


• The ELBO of Variational Autoencoders Converges to a Sum of Entropies
  Damm, Simon; Forster, Dennis; Velychko, Dmytro; Dai, Zhenwen; Fischer, Asja; Lücke, Jörg


• Autoencoded sparse Bayesian in-IRT factorization, calibration, and amortized inference for the Work Disability Functional Assessment Battery
  Chang, Joshua C; Chow , Carson C; Porcino, Julia


• Generalized PTR: User-Friendly Recipes for Data-Adaptive Algorithms with Differential Privacy
  Redberg, Rachel; Zhu, Yuqing; Wang, Yu-Xiang


• Provably Efficient Reinforcement Learning via Surprise Bound
  Zhu, Hanlin; Wang, Ruosong; Lee, Jason


• FAIR: Fair Collaborative Active Learning with Individual Rationality for Scientific Discovery
  Xu, Xinyi; Wu, Zhaoxuan; Verma, Arun; Foo, Chuan Sheng; Low, Bryan Kian Hsiang


• Learning a Schrödinger Bridge
  Stromme, Austin


• A Multi-Task Gaussian Process Model for Inferring Time-Varying Treatment Effects in Panel Data
  Chen, Yehu; Garnett, Roman; Montgomery, Jacob M; Prati, Annamaria


• Deep Grey-Box Models With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models
  Takeishi, Naoya; Kalousis, Alexandros


• Active Learning for Single Neuron Models with Lipschitz Non-Linearities
  Gajjar, Aarshvi; Musco, Christopher; Hegde, Chinmay


• Exploration in Reward Machines with Low Regret
  Bourel, Hippolyte; Jonsson, Anders; Maillard, Odalric; Talebi, Mohammad Sadegh


• On Universal Portfolios with Continuous Side Information
  Bhatt, Alankrita; Ryu, Jongha J; Kim, Young-Han


• Likelihood-Based Generative Radiance Field with Latent Space Energy-Based Model for 3D-Aware Disentangled Image Representation
  zhu, yaxuan; Xie, Jianwen; Li, Ping


• The Lauritzen-Chen Likelihood For Graphical Models
  Shpitser, Ilya


• Bayesian Strategy-Proof Facility Location via Robust Estimation
  Zampetakis, Emmanouil; Zhang, Fred


• Unsupervised representation learning with recognition-parametrised probabilistic models
  Walker, William I; Soulat, Hugo; Yu, Changmin; Sahani, Maneesh


• Universal Agent Mixtures and the Geometry of Intelligence
  Alexander, Samuel A; Quarel, David; Du, Len; Hutter, Marcus


• The communication cost of security and privacy in federated frequency estimation
  Chen, Wei-Ning; Ozgur, Ayfer; Cormode, Graham; Bharadwaj, Akash


• Learning While Scheduling in Multi-Server Systems With Unknown Statistics: MaxWeight with Discounted UCB
  Yang, Zixian; Srikant, R; Ying, Lei


• Piecewise Stationary Bandits under Risk Criteria
  Bhatt, Sujay; Fang, Guanhua; Li, Ping


• Does Label Differential Privacy Prevent Label Inference Attacks?
  Wu, Ruihan; Zhou, Jin Peng; Weinberger, Kilian; Guo, Chuan


• Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data
  Nakada, Ryumei; Gulluk, Halil Ibrahim; Deng, Zhun; Ji, Wenlong; Zou, James; Zhang, Linjun


• Conjugate Gradient Method for Generative Adversarial Networks
  Naganuma, Hiroki; Iiduka, Hideaki


• Subset verification and search algorithms for causal DAGs
  Choo, Davin; Shiragur, Kirankumar


• Distributed Offline Policy Optimization Over Batch Data
  Shen, Han ; Lu, Songtao; Cui, Xiaodong; Chen, Tianyi


• Decoupling Demographic Groups from Their Social Bias:\\An Approach for Fairness in Text Generation
  Wang, Rui; Cheng, Pengyu; Henao, Ricardo


• Learning Sparse Graphon Mean Field Games
  Fabian, Christian; Cui, Kai; Koeppl, Heinz


• Temporal Graph Neural Networks for Irregular Data
  Oskarsson, Joel; Sidén, Per; Lindsten, Fredrik


• Oblivious near-optimal sampling for multidimensional signals with Fourier constraints
  Xu, Xingyu; Gu, Yuantao


• Gaussian Processes on Finite Spaces of Graphs
  Borovitskiy, Viacheslav; Karimi, Mohammad Reza; Somnath, Vignesh Ram; Krause, Andreas


• A Tale of Sampling and Estimation in Discounted Reinforcement Learning
  Metelli, Alberto Maria; Mutti, Mirco; Restelli, Marcello


• Mean Parity Fair Regression in RKHS
  Wei, Shaokui; Liu, Jiayin; Li, Bing; Zha, Hongyuan


• A Unified Perspective on Regularization and Perturbation in Differentiable Subset Selection
  SUN, Xiangqian; Leung, Cheuk Hang; Li, Yijun; Wu, Qi


• Nystrom Method for Accurate and Scalable Implicit Differentiation
  Hataya, Ryuichiro; Yamada, Makoto


• Fair Representation Learning with Unreliable Labels
  Zhang, Yixuan; Zhou, Feng; Li, Zhidong; Wang, Yang; Chen, Fang


• Neural discovery of permutation subgroups
  Karjol, Pavan; Kashyap, Rohan; A P, Prathosh


• Feasible Recourse Plan via Diverse Interpolation
  Nguyen, Duy; Bui, Ngoc; Nguyen, Viet Anh


• Computing Abductive Explanations for Boosted Trees
  Audemard, Gilles; Lagniez, Jean-Marie; Marquis, Pierre; szczepanski, Nicolas


• A Statistical Learning Take on the Concordance Index for Survival Analysis
  Elgui, Kevin; Nowak, Alex; Robin, Geneviève


• An Efficient and Continuous Voronoi Density Estimator
  Marchetti, Giovanni Luca; Polianskii, Vladislav; Varava, Anastasiia; Pokorny, Florian T.; Kragic, Danica


• Equivariant Representation Learning via Class-Pose Decomposition
  Marchetti, Giovanni Luca; Tegnér, Gustaf; Varava, Anastasiia; Kragic, Danica


• Approximating a RUM from Distributions on $k$-Slates
  Chierichetti, Flavio; Giacchini, Mirko; Kumar, Ravi; Panconesi, Alessandro; Tomkins, Andrew


• Mediated Uncoupled Learning and Validation with Bregman Divergences: Loss Family with Maximal Generality
  Yamane, Ikko; Chevaleyre, Yann; Ishida, Takashi; Yger, Florian


• Coordinate Descent for SLOPE
  Larsson, Johan; Klopfenstein, Quentin; Massias, Mathurin; Wallin, Jonas


• Multi-task Representation Learning with Stochastic Linear Bandits
  Cella, Leonardo; Lounici, Karim; Pacreau, Gregoire; Pontil, Massimiliano


• A Sea of Words: An In-Depth Analysis of Anchors for Text Data
  Lopardo, Gianluigi; Garreau, Damien; Precioso, Frederic


• Robust Sequential Testing and Effect Estimation in Stratified Count Data
  Turner, Rosanne; Grunwald, Peter


• High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent
  Mangold, Paul; Bellet, Aurélien; Salmon, Joseph; Tommasi, Marc


• On Generalization of Decentralized Learning with Separable Data
  Taheri, Hossein; Thrampoulidis, Christos


• Neural Simulated Annealing
  Correia, Alvaro H. C.; Worrall, Daniel E; Bondesan, Roberto


• Adaptation to Misspecified Kernel Regularity in Kernelised Bandits
  Liu, Yusha; Singh, Aarti


• Gaussian Processes on Distributions based on Regularized Optimal Transport
  Bachoc, Francois; Béthune, Louis; González Sanz, Alberto; Loubes, Jean-Michel


• Optimal Contextual Bandits with Knapsacks under Realizibility via Regression Oracles
  Han, Yuxuan; Zeng, Jialin; Wang, Yang; Xiang, Yang; Zhang, Jiheng


• Bounding Evidence and Estimating Log-Likelihood in VAE
  Struski, Łukasz; Mazur, Marcin; Batorski, Paweł; Spurek, PRzemysław; Tabor, Jacek


• Privacy-preserving Sparse Generalized Eigenvalue Problem
  Hu, Lijie; Xiang, Zihang; Liu, Jiabin; Wang, Di


• Asymptotic Bayes risk of semi-supervised multitask learning on Gaussian mixture
  Nguyen, Minh-Toan; Couillet, Romain


• Manifold Restricted Interventional Shapley Values
  Taufiq, Muhammad Faaiz; Blöbaum, Patrick; Minorics, Lenon


• A Variance-Reduced and Stabilized Proximal Stochastic Gradient Method with Support Identification Guarantees for Structured Optimization
  Dai, Yutong; Wang, Guanyi; Robinson, Daniel P; Curtis, Frank


• Scalable particle-based alternatives to EM
  Kuntz Nussio, Juan; Lim, Jen Ning; Johansen, Adam M.


• Complex-to-Real Random Features for Polynomial Kernels
  Wacker, Jonas; Ohana, Ruben; Filippone, Maurizio


• Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation
  Moss, Henry B; Ober, Sebastian W; Picheny, Victor


• Nonmyopic Multiclass Active Search with Diminishing Returns for Diverse Discovery
  Nguyen, Quan; Garnett, Roman


• Efficient fair PCA for fair representation learning
  Kleindessner, Matthäus; Donini, Michele; Russell, Chris; Zafar, Muhammad Bilal


• Unified Perspective on Probability Divergence via the Density-Ratio Likelihood: Bridging KL-Divergence and Integral Probability Metrics
  Kato, Masahiro; Imaizumi, Masaaki; Minami, Kentaro


• Federated Averaging Langevin Dynamics: Toward a unified theory of and new algorithms
  Plassier, Vincent; Moulines, Eric; Durmus, Alain


• Adversarial Random Forests for Density Estimation and Generative Modelling
  Watson, David; Blesch, Kristin; Kapar, Jan; Wright, Marvin N


• Smoothly Giving up: Robustness for Simple Models
  Sypherd, Tyler; Stromberg, Nathaniel; Nock, Richard; Berisha, Visar; Sankar, Lalitha


• A Tighter Problem-Dependent Regret Bound for Risk-Sensitive Reinforcement Learning
  Hu, Xiaoyan; Leung, Ho-fung


• Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation
  Patil, Gandharv; L.A., Prashanth; Nagaraj, Dheeraj M; Precup, Doina


• Implications of sparsity and high triangle density for graph representation learning
  Sansford, Hannah J; Modell, Alexander; Whiteley, Nick; Rubin-Delanchy, Patrick


• Asymptotically Unbiased Off-Policy Policy Evaluation when Reusing Old Data in Nonstationary Environments
  Liu, Vincent; Chandak, Yash; Thomas, Philip; White, Martha


• Is interpolation benign for random forest regression?
  Arnould, Ludovic; Boyer, Claire; Scornet, Erwan


• TabLLM: Few-shot Classification of Tabular Data with Large Language Models
  Hegselmann, Stefan; Buendia, Alejandro; Lang, Hunter; Agrawal, Monica N; Jiang, Xiaoyi; Sontag, David


• A Faster Sampler for Discrete Determinantal Point Processes
  Tremblay, Nicolas; barthelmé, simon; Amblard, Pierre-Olivier


• Faithful Heteroscedastic Regression with Neural Networks
  Stirn, Andrew; Wessels, Harm; Schertzer, Megan; Pereira, Laura; Sanjana, Neville; Knowles, David


• Boosted Off-Policy Learning
  London, Ben; Lu, Levi(Chenhui); Sandler, Ted; Joachims, Thorsten


• Symmetric (Optimistic) Natural Policy Gradient for Multi-Agent Learning with Parameter Convergence
  Pattathil, Sarath; Zhang, Kaiqing; Ozdaglar, Asuman


• A Contrastive Approach to Online Change Point Detection
  Puchkin, Nikita; Shcherbakova, Valeriia


• Active Membership Inference Attack under Local Differential Privacy in Federated Learning
  Nguyen, Truc; Lai, Phung; Tran, Khang; Phan, Hai; Thai, My T.


• Differentially Private Matrix Completion through Low-rank Matrix Factorization
  Wang, Lingxiao; Zhao, Boxin; Kolar, Mladen


• Private Non-Convex Federated Learning Without a Trusted Server
  Lowy, Andrew; Ghafelebashi, Ali; Razaviyayn, Meisam


• Variational Boosted Soft Trees
  Cinquin, Tristan ; Rukat, Tammo; Schmidt, Philipp; Wistuba, Martin; Bekasov, Artur


• The Schrödinger Bridge between Gaussian Measures has a Closed Form
  Bunne, Charlotte; Hsieh, Ya-Ping; Cuturi, marco; Krause, Andreas


• Federated Learning under Distributed Concept Drift
  Jothimurugesan, Ellango; Hsieh, Kevin; Wang, Jianyu; Joshi, Gauri; Gibbons, Phillip B


• Cooperative Inverse Decision Theory for Uncertain Preferences
  Robertson, Zachary; Zhang, Hantao; Koyejo, Sanmi


• Falsification of Internal and External Validity in Observational Studies via Conditional Moment Restrictions
  Hussain, Zeshan M; Shih, Ming-Chieh; Oberst, Michael; Demirel, Ilker; Sontag, David


• Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification
  Hu, Yuqing; Pateux, Stephane; Gripon, Vincent


• Heavy Sets with Applications to Interpretable Machine Learning Diagnostics
  Malioutov, Dmitry M; Dash, Sanjeeb; Wei, Dennis


• Stochastic Mirror Descent for Large-Scale Sparse Recovery
  Ilandarideva, Sasila; Bekri, Yannis; Iouditski, Anatoli; Perchet, Vianney


• High Probability Bounds for Stochastic Continuous Submodular Maximization
  Becker, Evan; Gao, Jingdong; Zadouri, Ted; Mirzasoleiman, Baharan


• Average Adjusted Association: Efficient Estimation with High Dimensional Confounders
  Jun, Sung Jae; Lee, Sokbae


• Reinforcement Learning for Adaptive Mesh Refinement
  Yang, Jiachen; Dzanic, Tarik; Petersen, Brenden K; Kudo, Jun; Mittal, Ketan; Tomov, Vladimir; Camier, Jean-Sylvain; Zhao, Tuo; Zha, Hongyuan; Kolev, Tzanio; Anderson, Robert; Faissol, Daniel


• Risk Bounds on Aleatoric Uncertainty Recovery
  Lin, Jiahe; Zhang, Yikai; LI, FENGPEI; Adler, Yeshaya; Rasul, Kashif; Schneider, Anderson L; Nevmyvaka, Yuriy


• Robust and Agnostic Learning of Conditional Distributional Treatment Effects
  Kallus, Nathan; Oprescu, Miruna


• Optimism and Delays in Episodic Reinforcement Learning
  Howson, Benjamin M; Pike-Burke, Ciara M; Filippi, Sarah


• Delayed Feedback in Generalised Linear Bandits Revisited
  Howson, Benjamin M; Pike-Burke, Ciara M; Filippi, Sarah


• Stochastic Tree Ensembles for Estimating Heterogeneous Effects
  Krantsevich, Nikolay; He, Jingyu; Hahn, P. Richard


• Minimax Nonparametric Two-Sample Test under Adversarial Losses
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• Dimensionality Collapse: Optimal Measurement Selection for Low-Error Infinite-Horizon Forecasting
  Naumer, Helmuth; Kamalabadi, Farzad


• Distill n' Explain: explaining graph neural networks using simple surrogates
  Pereira , Tamara Arruda; Nascimento, Erik J; Resck, Lucas E; Mesquita, Diego; Souza, Amauri


• Nonstationary Bandit Learning via Predictive Sampling
  Liu, Yueyang; Van Roy, Benjamin; Xu, Kuang


• Continuous-Time Decision Transformer for Healthcare Applications
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• Dueling RL: Reinforcement Learning with Trajectory Preferences
  Saha, Aadirupa; Pacchiano, Aldo; Lee, Jonathan


• Discrete Langevin Samplers via Wasserstein Gradient Flow
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• Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion
  Ju, Haotian; Li, Dongyue; Sharma, Aneesh; Zhang, Hongyang R


• Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning
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• NODAGS-Flow: Nonlinear Cyclic Causal Structure Learning
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• Data Banzhaf: A Robust Data Valuation Framework for Machine Learning
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• Revisiting Fair-PAC Learning and the Axioms of Cardinal Welfare
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• Distributionally Robust Policy Gradient for Offline Contextual Bandits
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• A stopping criterion for Bayesian optimization by the gap of expected minimum simple regrets
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• LOFT: Finding Lottery Tickets through Filter-wise Training
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• Provably Efficient Model-Free Algorithms for Non-stationary CMDPs
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• Precision Recall Cover: A Method For Assessing Generative Models
  Cheema, Fasil T; Urner, Ruth


• Reconstructing Training Data from Model Gradient, Provably
  Wang, Zihan; Lee, Jason; Lei, Qi


• Scalable Spectral Clustering with Group Fairness Constraints
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• Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout
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• Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection
  Cong, Weilin; Mahdavi, Mehrdad


• Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach
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• Uncertainty-aware Unsupervised Video Hashing
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• Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach
  Raj, Vishnu; Cui, Tianyu; Heinonen, Markus; Marttinen, Pekka


• Structure of Nonlinear Node Embeddings in Stochastic Block Models
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• On Model Selection Consistency of Lasso for High-Dimensional Ising Models
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• Optimal Sample Complexity Bounds for Non-convex Optimization under Kurdyka-Lojasiewicz Condition
  Yu, Qian; Wang, Yining; Huang, Baihe; Lei, Qi; Lee, Jason D


• INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation
  Liu, Ning; Yu, Yue; You, Huaiqian; Tatikola, Neeraj K


• Transport Reversible Jump Proposals
  Davies, Laurence S; Salomone, Robert; Sutton, Matthew; Drovandi, Chris


• Convex Bounds on the Softmax Function with Applications to Robustness Verification
  Wei, Dennis; Wu, Haoze; Wu, Min; Chen, Pin-Yu; Barrett, Clark; Farchi, Eitan


• Strong Lottery Ticket Hypothesis with $\varepsilon$--perturbation
  Xiong, Zheyang; Liao, Fangshuo; Kyrillidis, Anastasios


• Two-Sample Tests for Inhomogeneous Random Graphs in $L_r$ norm: Optimality and Asymptotics
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• Indeterminacy in Generative Models: Characterization and Strong Identifiability
  Xi, Quanhan; Bloem-Reddy, Benjamin


• Differentiable Change point Detection With Temporal Point Processes
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• Recurrent Neural Networks and Universal Approximation of Bayesian Filters
  Bishop, Adrian; Bonilla, Edwin V.


• Thresholded linear bandits
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• Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary based Randomized Continuous Embeddings
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• Unifying local and global model explanations by functional decomposition of low dimensional structures
  Hiabu, Munir; Meyer, Joseph T.; Wright, Marvin N


• SMCP3: SMC with Probabilistic Program Proposals
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• On double-descent in uncertainty quantification in overparametrized models
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• Learning Treatment Effects from Observational and Experimental Data
  Triantafillou, Sofia; Jabbari, Fattaneh; Cooper, Gregory F


• On the Accelerated Noise-Tolerant Power Method
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• Clustering High-dimensional Data with Ordered Weighted L1 Regularization
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• Flexible and Efficient Contextual Bandits with Heterogeneous Treatment Effect Oracles
  Carranza, Aldo G; Krishnamurthy, Sanath Kumar; Athey, Susan


• Faster Projection-Free Augmented Lagrangian Methods via Weak Proximal Oracle
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• Meta-Learning with Adjoint Methods
  Li, Shibo; Wang, Zheng; Narayan, Akil; Kirby, Robert; Zhe, Shandian


• Combining Graphical and Algebraic Approaches for Parameter Identification in Latent Variable Structural Equation Models
  Ankan, Ankur; Wortel, Inge; Bollen, Kenneth; Textor, Johannes


• Explicit Regularization in Overparametrized Models via Noise Injection
  Orvieto, Antonio; Raj, Anant; Kersting, Hans; Bach, Francis


• Efficient Informed Proposals for Discrete Distributions via Newton’s Series Approximation
  Xiang, Yue; Zhu, Dongyao; Lei, Bowen; Xu, Dongkuan; Zhang, Ruqi


• An Homogeneous Unbalanced Regularized Optimal Transport model with applications to Optimal Transport with Boundary
  Lacombe, Theo


• Prediction-Oriented Bayesian Active Learning
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• Active Exploration via Experiment Design in Markov Chains
  Mutny, Mojmir; Janik, Tadeusz; Krause, Andreas


• But Are You Sure? An Uncertainty-Aware Perspective on Explainable AI
  Marx, Charles; Park, Youngsuk; Hasson, Hilaf; Wang, Yuyang; Ermon, Stefano; Huan, Luke


• Identification of Blackwell Optimal Policies for Deterministic MDPs
  Boone, Victor; Gaujal, Bruno


• Multi-Fidelity Bayesian Optimization with Unreliable Information Sources
  Mikkola, Petrus; Martinelli, Julien; Filstroff, Louis; Kaski, Samuel


• Randomized Greedy Learning for Non-monotone Stochastic Submodular Maximization Under Full-bandit Feedback
  Fourati, Fares; Aggarwal, Vaneet; Quinn, Christopher; Alouini , Mohamed-Slim


• Protecting Global Properties of Datasets with Distribution Privacy Mechanisms
  Chen, Michelle G; Ohrimenko, Olga


• Incremental Aggregated Riemannian Gradient Method for Distributed PCA
  Wang, Xiaolu; Jiao, Yuchen; Wai, Hoi-To; Gu, Yuantao


• Minimax-Bayes Reinforcement Learning
  Kleine Buening, Thomas; Dimitrakakis, Christos; Eriksson, Hannes; Grover, Divya; Jorge, Emilio


• Retrospective Uncertainties for Deep Models using Vine Copulas
  Tagasovska, Natasa; Ozdemir, Firat; Brando, Axel


• Optimal Algorithms for Latent Bandits with Cluster Structure
  Pal, Soumyabrata ; Suggala, Arun Sai ; Shanmugam, Karthikeyan; Jain, Prateek


• Improved Bound on Generalization Error of Compressed KNN Estimator
  zhang, hang; Li, Ping


• Streaming Sparse Linear Regression
  Yang, Shuoguang; Yan, Yuhao; Zhu, Xiuneng; Sun, Qiang


• Multi-Agent congestion cost minimization with linear function approximation
  Trivedi, Prashant; Hemachandra, Nandyala


• Global-Local Regularization Via Distributional Robustness
  Phan, Hoang; Le, Trung; Phung, Trung Q; Bui, Anh Tuan; Ho, Nhat; Phung, Dinh


• Vector Quantized Time Series Modeling with a Bidirectional Prior Model
  Lee, Daesoo; Malacarne, Sara; Aune, Erlend


• Do Bayesian Neural Networks Need to be Fully Stochastic?
  Sharma, Mrinank; Farquhar, Sebastian; Nalisnick, Eric; Rainforth, Tom


• Risk-aware linear bandits with convex loss
  Saux, Patrick; Maillard, Odalric


• One Arrow, Two Kills: An Unified Framework for Achieving Optimal Regret Guarantees for Sleeping Bandits
  Saha, Aadirupa; Gaillard, Pierre; Dan, Soham


• Data Augmentation for Imbalanced Regression
  Stocksieker, Samuel; Pommeret, Denys; Charpentier, Arthur


• Fast Feature Selection with Fairness Constraints
  Quinzan, Francesco; Khanna, Rajiv; Hershcovitch, Moshik; Cohen, Sarel; Waddington, Daniel G; Friedrich, Tobias; Mahoney, Michael


• On the Consistency Rate of Decision Tree Learning Algorithms
  Zheng, Qin-Cheng; Lyu, Shen-Huan; Zhang, Shao-Qun; Jiang, Yuan; Zhou, Zhi-Hua


• Ranked-Based Causal Discovery for Post-Nonlinear Models
  Keropyan, Grigor; Strieder, David; Drton, Mathias


• On the Complexity of Representation Learning in Contextual Linear Bandits
  Tirinzoni, Andrea; Pirotta, Matteo; Lazaric, Alessandro


• Hierarchical-Hyperplane Kernels for Actively Learning Gaussian Process Models of Nonstationary Systems
  Bitzer, Matthias; Meister, Mona; Zimmer, Christoph


• Revisiting Weighted Strategy for Non-stationary Parametric Bandits
  Wang, Jing; Zhao, Peng; Zhou, Zhi-Hua


• No time to waste: practical statistical contact tracing with few low-bit messages
  Romijnders, Rob; Asano, Yuki M; Louizos, Christos; Welling, Max


• Understanding the Impact of Competing Risks on Heterogeneous Treatment Effect Estimation from Time-to-Event Data
  Curth, Alicia; van der Schaar, Mihaela


• Performative Prediction in the Presence of Corruptions
  Shan, Jia-Wei; Zhao, Peng; Zhou, Zhi-Hua


• Last-Iterate Convergence with Full- and Noisy-Information Feedback in Two-Player Zero-Sum Games
  Abe, Kenshi; Ariu, Kaito; Sakamoto, Mitsuki; Toyoshima, Kentaro; Iwasaki, Atsushi


• Model-Based Uncertainty in Value Functions
  Luis, Carlos E.; Bottero, Alessandro G; Vinogradska, Julia; Berkenkamp, Felix; Peters, Jan


• The Role of Codeword-to-Class Assignments in Error Correcting Codes: An Empirical Study
  Onn, Ophir; Weiss, Tamar; Azeroual, Hai; Soudry, Daniel; Evron, Itay


• Online Algorithms with Costly Predictions
  Drygala, Marina R; Nagarajan, Sai Ganesh; Svensson, Ola


• Adaptive Tuning for Metropolis Adjusted Langevin Trajectories
  Riou-Durand, Lionel; Sountsov, Pavel; Vogrinc, Jure; Margossian, Charles; Power, Sam


• Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits
  Tsuchiya, Taira; Ito, Shinji; Honda, Junya


• PAC-Bayesian Learning of Optimization Algorithms
  Sucker, Michael; Ochs, Peter


• Tighter PAC-Bayes Generalisation Bounds by Leveraging Example Difficulty
  Biggs, Felix; Guedj, Benjamin


• Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery
  Maunu, Tyler; Le Gouic, Thibaut; Rigollet, Philippe


• Sampling uncertainties on the Precision-Recall curve
  Baak, Max; Collot, Stéphane; Fridman Rojas, Ilan; Urlus, Ralph E.Q.


• Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference
  Banerjee, Debangshu; Ghosh, Avishek; Ray Chowdhury, Sayak; Gopalan, Aditya


• Nothing but Regrets --- Privacy-Preserving Federated Causal Discovery
  Mian, Osman A; Kaltenpoth, David; Kamp, Michael; Vreeken, Jilles


• Nonparametric Gaussian Process Covariances via Multidimensional Convolutions
  McDonald, Thomas M; Ross, Magnus ; Smith, Michael T; Álvarez, Mauricio A


• Improved Representation Learning Through Tensorized Autoencoders
  Esser, Pascal M; Mukherjee, Satyaki; Sabanayagam, Mahalakshmi; Ghoshdastidar, Debarghya


• Tensor-based Kernel Machines with Structured Inducing Points for Large and High-Dimensional Data
  Wesel, Frederiek; Batselier, Kim


• Mode-Seeking Divergences: Theory and Applications to GANs
  Li, Cheuk Ting; Farnia, Farzan


• A Targeted Accuracy Diagnostic for Variational Approximations
  Wang, Yu; Kasprzak, Mikolaj J; Huggins, Jonathan H


• Fix-A-Step: Semi-supervised Learning From Uncurated Unlabeled Data
  Huang, Zhe; Sidhom, Mary-Joy; Wessler, Benjamin; Hughes, Michael C


• Root Cause Identification for Collective Anomalies given a Summary Causal Graph and Time Series
  ASSAAD, Charles K.; Ez-zejjari, Imad; ZAN, Lei


• Principled Approaches for Private Adaptation from a Public Source
  Bassily, Raef; Mohri, Mehryar; Suresh, Ananda Theertha


• CLIP-Lite: Information Efficient Visual Representation Learning with Language Supervision
  Shrivastava, Aman; R. Selvaraju, Ramprasaath; Naik, Nikhil; Ordonez, Vicente


• Surveillance Evasion Through Bayesian Reinforcement Learning
  Qi, Dongping; Bindel, David; Vladimirsky, Alexander


• Random feature ridge regression in the overparameterized regime with a general dataset
  Wang, Zhichao; Zhu, Yizhe


• How Does Pseudo-Labeling Affect the Generalization Error of the Semi-Supervised Gibbs Algorithm?
  He, Haiyun; Aminian, Gholamali; Bu, Yuheng; Rodrigues, Miguel; Tan, Vincent


• Scalable Unbalanced Sobolev Transport for Measures on a Graph
  Le, Tam; Nguyen, Truyen; Fukumizu, Kenji


• Discrete Distribution Estimation under User-level Local Differential Privacy
  Acharya, Jayadev; Liu, Yuhan; Sun, Ziteng


• Causal Entropy Optimization
  Branchini, Nicola; Aglietti, Virginia; Dhir, Neil; Damoulas, Theodoros


• Loss Curvature Matching for Dataset Selection and Condensation
  Shin, Seungjae; BAE, HeeSun; Shin, DongHyeok; Joo, Weonyoung; Moon, Il-Chul


• Wasserstein Distributionally Robust Linear-Quadratic Estimation under Martingale Constraints
  Lotidis, Kyriakos; Bambos, Nicholas; Blanchet, Jose; Li, Jiajin


• Density Ratio Estimation and Neyman Pearson Classification with Missing Data
  Givens, Josh L; Reeve, Henry W. J. ; Liu, Song


• Rethinking Initialization of the Sinkhorn Algorithm
  Thornton, James; Cuturi, marco


• Representation Learning in Deep RL via Discrete Information Bottleneck
  Islam, Riashat; Zang, Hongyu; Tomar, Manan; Didolkar, Aniket Rajiv; Islam, Md Mofijul; Goyal, Anirudh; Arnob, Samin Yeasar; Li, Xin; Iqbal, Tariq; Heess, Nicolas; Lamb, Alex


• Learning Robust Graph Neural Networks with Limited Supervision
  Alchihabi, Abdullah; Guo, Yuhong


• Consistent Complementary-Label Learning via Order-Preserving Losses
  Liu, Shuqi; Cao, Yuzhou; Zhang, Qiaozhen; Feng, Lei; An, Bo


• Tight Regret and Complexity Bounds for Thompson Sampling via Langevin Monte Carlo
  Huix, Tom tom; Zhang, Shunshi; Durmus, Alain


• Nonstochastic Contextual Combinatorial Bandits
  Zierahn, Lukas; van der Hoeven, Dirk; Cesa-Bianchi, Nicolò; Neu, Gergely


• Probabilistic Conformal Prediction Using Conditional Random Samples
  Wang, Zhendong; Gao, Ruijiang; Yin, Mingzhang; Zhou, Mingyuan; Blei, David


• Preferential Subsampling for Stochastic Gradient Langevin Dynamics
  Putcha, Srshti; Nemeth, Christopher; Fearnhead, Paul


• Calibration of Probabilistic Classifier Sets
  Mortier, Thomas; Bengs, Viktor; Hüllermeier, Eyke; Luca, Stijn; Waegeman, Willem


• Context-Specific Causal Discovery for Categorical Data Using Staged Trees
  Leonelli, Manuele; Varando, Gherardo


• Federated Learning for Data Streams
  Marfoq, Othmane; Vidal, Richard; Neglia, Giovanni; Kameni, Laetitia


• Combating label-leaking explanations
  Jethani, Neil; Saporta, Adriel; Ranganath, Rajesh


• Adversarial robustness of VAEs through the lens of local geometry
  Khan, Asif; Storkey, Amos


• Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise
  Ye, Haotian; Zou, James; Zhang, Linjun


• Learning to Optimize for Stochastic Dominance Constraints
  Dai, Hanjun; Xue, Yuan; He, Niao; Wang, Yixin; Li, Na; Schuurmans, Dale; Dai, Bo


• SoundSynp: Sound Source Detection from Raw Waveforms with Multi-Scale Synperiodic Filterbanks
  He, Yuhang; Markham, Andrew


• Second Order Path Variationals in Non-Stationary Online Learning
  Baby, Dheeraj; Wang, Yu-Xiang


• Bayesian Optimization Over Iterative Learners with Structured Responses: A Budget-aware Planning Approach
  Belakaria, Syrine; Doppa, Janardhan Rao; Fusi, Nicolo; Sheth, Rishit


• Knowledge Sheaves: A Sheaf-Theoretic Framework for Knowledge Graph Embedding
  Gebhart, Thomas; Hansen, Jakob; Schrater, Paul


• Active Cost-aware Labeling of Streaming Data
  Cai, Ting; Kandasamy, Kirthevasan


• Krylov--Bellman boosting: Super-linear policy evaluation in general state spaces
  Xia, Eric; Wainwright, Martin


• SwAMP: Swapped Assignment of Multi-Modal Pairs for Cross-Modal Retrieval
  Kim, Minyoung


• A Mini-Block Fisher Method for Deep Neural Networks
  Bahamou, Achraf; Goldfarb, Donald; Ren, Yi


• Origins of Low-Dimensional Adversarial Perturbations
  Dohmatob, Elvis; Guo, Chuan; Goibert, Morgane


• On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network
  Gao, Hongchang; Gu, Bin; Thai, My T.


• Pricing against a Budget and ROI Constrained Buyer
  Golrezaei, Negin; Jaillet , Patrick; Liang, Jason Cheuk Nam; Mirrokni, Vahab


• Improving Dual-Encoder Training Through Dynamic Indexes for Negative Mining
  Monath, Nicholas; Zaheer, Manzil; Allen, Kelsey; McCallum, Andrew


• Incentive-aware Contextual Pricing with Non-parametric Market Noise
  Golrezaei, Negin; Jaillet , Patrick; Liang, Jason Cheuk Nam


• Coherent Probabilistic Forecasting of Temporal Hierarchies
  Rangapuram, Syama Sundar; Kapoor, Shubham; Nirwan, Rajbir S; Mercado, Pedro; Januschowski, Tim ; Wang, Yuyang; Bohlke-Schneider, Michael


• Optimal robustness-consistency tradeoffs for learning-augmented metrical task systems
  Christianson, Nicolas; Shen, Junxuan; Wierman, Adam


• Randomized geometric tools for anomaly detection in stock markets
  Bachelard, Cyril; Chalkis, Apostolos; Fisikopoulos, Vissarion; Tsigaridas, Elias


• ForestPrune: Compact Depth-Pruned Tree Ensembles
  Liu, Brian; Mazumder, Rahul


• Instance-dependent Bounds for Zero-sum Matrix Games
  Maiti, Arnab; Jamieson, Kevin; Ratliff, Lillian


• Multiple-policy High-confidence Policy Evaluation
  Dann, Chris; Ghavamzadeh, Mohammad; Marinov, Teodor Vanislavov


• Scalable Probabilistic and Causal Inference using Tractable Circuit Models
  Wang, Benjie; Kwiatkowska, Marta


• Improved Approximation for Fair Correlation Clustering
  Ahmadian, Sara; Negahbani, Maryam


• Scalable Bicriteria Algorithms for Non-Monotone Submodular Cover
  Crawford, Victoria


• Diffusion Generative Models in Infinite Dimensions
  Kerrigan, Gavin; Ley, Justin S; Smyth, Padhraic


• MMD-B-Fair: Learning Fair Representations with Statistical Testing
  Deka, Namrata; Sutherland, Danica J.


• Domain Adaptation under Missingness Shift---Tackling Underreporting
  Zhou, Helen; Balakrishnan, Sivaraman; Lipton, Zachary


• Nash Equilibria and Pitfalls of Adversarial Training in Adversarial Robustness Games
  Balcan, Maria-Florina; Pukdee, Rattana; Ravikumar, Pradeep ; Zhang, Hongyang


• Adapting to Latent Subgroup Shifts via Concepts and Proxies
  Alabdulmohsin, Ibrahim; Chiou, Nicole; D'Amour, Alexander; Gretton, Arthur; Koyejo, Sanmi; Kusner, Matt J; Pfohl, Stephen R; Salaudeen, Olawale; Schrouff, Jessica; Tsai, Katherine


• Huber-robust confidence sequences
  Wang, Hongjian; Ramdas, Aaditya


• On the Privacy Risks of Algorithmic Recourse
  Pawelczyk, Martin; Lakkaraju, Himabindu; Neel, Seth


• Reducing Discretization Error in the Frank-Wolfe Method
  Chen, Zhaoyue; Sun, Yifan


• Improved Sample Complexity Bounds for Distributionally Robust Reinforcement Learning
  Xu, Zaiyan; Panaganti, Kishan; Kalathil, Dileep


• Factorial SDE for Multi-Output Gaussian Process Regression
  Jeong, Daniel P; Kim, Seyoung


• Interactive Learning with Pricing for Optimal and Stable Allocations in Markets
  Erginbas, Yigit Efe; Phade, Soham; Ramchandran, Kannan


• Learning to Generalize Provably in Learning to Optimize
  Yang, Junjie; Chen, Tianlong; Zhu, Mingkang; He, Fengxiang; Tao, Dacheng; Liang, Yingbin; Wang, Zhangyang


• Theory and Algorithm for Batch Distribution Drift Problems
  Awasthi, Pranjal; Cortes, Corinna; Mohri, Christopher


• On The Convergence Of Policy Iteration-Based Reinforcement Learning With Monte Carlo Policy Evaluation
  Winnicki, Anna; Srikant, R


• Precision/Recall on Imbalanced Test Data
  Shang, Hongwei; Langlois, Jean-Marc; Tsioutsiouliklis, Kostas; Kang, Changsung


• Iterative Teaching by Data Hallucination
  Qiu, Zeju; Liu, Weiyang; Xiao, Tim Z; Liu, Zhen; Bhatt, Umang; Luo, Yucen; Weller, Adrian; Schölkopf, Bernhard


• Near-Optimal Differentially Private Reinforcement Learning
  Qiao, Dan; Wang, Yu-Xiang


• Doubly Fair Dynamic Pricing
  Xu, Jianyu; Qiao, Dan; Wang, Yu-Xiang


• Hedging against Complexity: Distributionally Robust Optimization with Parametric Approximation
  Iyengar, Garud; Lam, Henry; Wang, Tianyu


• Probabilities of Causation: Role of Observational Data
  Li, Ang; Pearl, Judea


• Influence Diagnostics under Self-concordance
  Fisher, Jillian R; Liu, Lang; Pillutla, Krishna; Choi, Yejin; Harchaoui, Zaid


• Theoretically Grounded Loss Functions and Algorithms for Adversarial Robustness
  Awasthi, Pranjal; Mao, Anqi; Mohri, Mehryar; Zhong, Yutao


• Large deviations rates for stochastic gradient descent with strongly convex functions
  Bajovic, Dragana; Jakovetic, Dusan; Kar, Soummya


• Stochastic Optimization for Spectral Risk Measures
  Mehta, Ronak; Liu, Lang; Pillutla, Krishna; Roulet, Vincent; Harchaoui, Zaid


• Improving adaptive conformal prediction using self-supervised learning
  Seedat, Nabeel; Jeffares, Alan; Imrie, Fergus; van der Schaar, Mihaela


• Oracle-free Reinforcement Learning in Mean-Field Games along a Single Sample Path
  ZAMAN, MUHAMMAD ANEEQ UZ; Koppel, Alec; Bhatt, Sujay; Basar, Tamer


• Sparsity-Inducing Categorical Prior Improves Robustness of the Information Bottleneck
  Samaddar, Anirban; Madireddy, Sandeep; Balaprakash, Prasanna; Maiti, Taps; de los Campos, Gustavo; Fischer, Ian


• Ideal Abstractions for Decision-Focused Learning
  Poli, Michael; Massaroli, Stefano; Ermon, Stefano ; Wilder, Bryan; Horvitz, Eric


• Probabilistic Querying of Continuous-Time Event Sequences
  Boyd, Alex J; Chang, Yuxin; Mandt, Stephan; Smyth, Padhraic


• Semantic Strengthening of Neuro-Symbolic Learning
  Ahmed, Kareem; Chang, Kai-Wei; Van den Broeck, Guy


• Fast Variational Estimation of Mutual Information for Implicit and Explicit Likelihood Models
  Dahlke, Caleb; Zheng, Sue; Pacheco, Jason


• SurvivalGAN: Generating time-to-event Data for Survival Analysis
  Norcliffe, Alexander LI; Cebere, Bogdan C; Imrie, Fergus; Lió, Pietro; van der Schaar, Mihaela


• A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem
  Jiang, Ruichen; Abolfazli, Nazanin; Mokhtari, Aryan; Yazdandoost Hamedani, Erfan


• Stochastic Methods for AUC Optimization subject to AUC-based Fairness Constraints
  Yao, Yao; Lin, Qihang; Yang, Tianbao


• DIET: Conditional independence testing with marginal dependence measures of residual information
  Sudarshan, Mukund; Puli, Aahlad; Tansey, Wesley; Ranganath, Rajesh


• Algorithm-Dependent Bounds for Representation Learning of Multi-Source Domain Adaptation
  CHEN, QI; Marchand, Mario


• Actually Sparse Variational Gaussian Processes
  Cunningham, Harry J; de Souza, Daniel A; Takao, So; van der Wilk, Mark; Deisenroth, Marc


• Competing against Adaptive Strategies in Online Learning via Hints
  Bhaskara, Aditya; Munagala, Kamesh


• ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images
  Hoffman, Matthew D; Sountsov, Pavel; Le, Tuan Anh; Lee, Ben; Suter, Christopher; Mansinghka, Vikash; A. Saurous, Rif


• Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier
  Compton, Spencer; Katz, Dmitriy A; Qi, Benjamin; Greenewald, Kristjan; Kocaoglu, Murat


• Automatic Attention Pruning: Improving and Automating Model Pruning using Attentions
  zhao, kaiqi; Jain, Animesh; Zhao, Ming


• Sample Complexity of Distinguishing Cause from Effect
  Acharya, Jayadev; Bhadane, Sourbh; Bhattacharyya, Arnab; Kandasamy, Saravanan; Sun, Ziteng


• Graph Spectral Embedding using the Geodesic Betweenness Centrality
  Deutsch, Shay; Soatto, Stefano


• Who Should Predict? Exact Algorithms For Learning to Defer to Humans
  Mozannar, Hussein; Lang, Hunter; Wei, Dennis; Sattigeri, Prasanna; Das, Subhro; Sontag, David


• Score-based Change Point Detection for Unnormalized Models
  Wu, Suya; Diao, Enmao; Banerjee, Taposh; Ding, Jie; Tarokh, Vahid


• Dropout-Resilient Secure Multi-Party Collaborative Learning with Linear Communication Complexity
  Lu, Xingyu XL; Sami, Hasin Us; Guler, Basak


• Reinforcement Learning with Step-wise Fairness Constraints
  Deng, Zhun; Sun, He; Wu, Steven; Zhang, Linjun; Parkes, David


• Implicit Graphon Neural Representation
  Xia, Xinyue; Mishne, Gal; Wang, Yusu


• Fitting low-rank models on egocentrically sampled partial networks
  Chan, Ga Ming Angus; Li, Tianxi


• Federated Asymptotics: a model to compare federated learning algorithms
  Cheng, Gary; Chadha, Karan; Duchi, John


• Conformalized Unconditional Quantile Regression
  Alaa, Ahmed; Hussain, Zeshan M; Sontag, David


• Wasserstein Distributional Learning via Majorization-Minimization
  Tang, Chengliang; Lenssen, Nathan; Wei, Ying; Zheng, Tian


• HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent
  Chen, Ziang; Lu, Jianfeng; Qian, Huajie; Wang, XInshang; Yin, Wotao


• Ultra-marginal Feature Importance: Learning from Data with Causal Guarantees
  Janssen, Joseph; Guan, Vincent; Robeva, Elina


• On the Implicit Geometry of Cross-Entropy Parameterizations for Label-Imbalanced Data
  Behnia, Tina; Kini, Ganesh Ramachandra; Vakilian, Vala; Thrampoulidis, Christos


• Convolutional Persistence as a Remedy to Neural Model Analysis
  Khramtsova, Ekaterina; Zuccon, Guido; Wang, Xi; Baktashmotlagh, Mahsa


• Uniformly Conservative Exploration in Reinforcement Learning
  Xu, Wanqiao; Ma, Yecheng; Xu, Kan; Bastani, Hamsa; Bastani, Osbert


• Provable Safe Reinforcement Learning with Binary Feedback
  Bennett, Andrew; Misra, Dipendra; Kallus, Nathan


• Balanced Off-Policy Evaluation for Personalized Pricing
  Elmachtoub, Adam; Gupta, Vishal; ZHAO, YUNFAN


• Provable Hierarchy-Based Meta-Reinforcement Learning
  Chua, Kurtland; Lei, Qi; Lee, Jason


• A Blessing of Dimensionality in Membership Inference through Regularization
  Tan, Jasper T; LeJeune, Daniel; Mason, Blake; Javadi, Hamid; Baraniuk, Richard


• Posterior Tracking Algorithm for Classification Bandits
  Tabata, Koji; Komiyama, Junpei; Nakamura, Atsuyoshi; Komatsuzaki, Tamiki


• The Power of Recursion in Graph Neural Networks for Counting Substructures
  Tahmasebi, Behrooz; Lim, Derek; Jegelka, Stefanie


• Mixtures of All Trees
  Selvam, Nikil R; Zhang, Honghua; Van den Broeck, Guy


• Improving Adversarial Robustness via Joint Classification and Multiple Explicit Detection Classes
  Baharlouei, Sina; Sheikholeslami, Fatemeh; Razaviyayn, Meisam; Kolter, Zico


• Performative Prediction with Neural Networks
  Mofakhami, Mehrnaz; Mitliagkas, Ioannis; Gidel, Gauthier


• Benign overfitting of non-smooth neural networks beyond lazy training
  Xu, Xingyu; Gu, Yuantao


• A New Modeling Framework for Continuous, Sequential Domains
  Dong, Hailiang; Amato, James C; Gogate, Vibhav; Ruozzi, Nicholas


• TS-UCB: Improving on Thompson Sampling With Little to No Additional Computation
  Baek, Jackie; Farias, Vivek


• Reward Learning as Doubly Nonparametric Bandits: Optimal Design and Scaling Laws
  Bhatia, Kush; Guo, Wenshuo; Steinhardt, Jacob


• Approximate Regions of Attraction in Learning with Decision-Dependent Distributions
  Dong, Roy; Ratliff, Lillian ; Zhang, Heling


• Randomized Primal-Dual Methods with Line-Search for Saddle Point Problems
  Yazdandoost Hamedani, Erfan; Jalilzadeh, Afrooz; Aybat, Necdet Serhat


• Spectral Augmentations for Graph Contrastive Learning
  Ghose, Amur; Zhang, Yingxue; Hao, Jianye; Coates, Mark


• Deep Value Function Networks for Large-Scale Multistage Stochastic Programming Problems
  Bae, Hyunglip; Lee, Jinkyu; Kim, Woo Chang; Lee, Yongjae


• Optimal Sketching Bounds for Sparse Linear Regression
  Mai, Tung; Munteanu, Alexander; Musco, Cameron; Rao, Anup; Schwiegelshohn, Chris; Woodruff, David


• Average case analysis of Lasso under ultra sparse conditions
  Okajima, Koki; Meng, Xiangming; Takahashi, Takashi; Kabashima, Yoshiyuki


• Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition
  Gruber, Sebastian; Buettner, Florian


• Collision Probability Matching Loss for Disentangling Epistemic Uncertainty from Aleatoric Uncertainty
  Narimatsu, Hiromi; Ozawa, Mayuko; Kumano, Shiro


• Random Features Model with General Convex Regularization: A Fine Grained Analysis with Precise Asymptotic Learning Curves
  Bosch, David; Panahi, Ashkan; Ozcelikkale, Ayca; Dubhashi, Devdatt


• Learning to Defer to Multiple Experts: Consistent Surrogate Losses, Confidence Calibration, and Conformal Ensembles
  Verma, Rajeev; Barrejon, Daniel; Nalisnick, Eric


• Spread Flows for Manifold Modelling
  Zhang, Mingtian; Sun, Yitong; Zhang, Chen; McDonagh, Steven


• Breaking a Classical Barrier for Classifying Arbitrary Test Examples in the Quantum Model
  Gluch, Grzegorz; Barooti, Khashayar; Urbanke, Rüdiger


• Characterizing Polarization in Social Networks using the Signed Relational Latent Distance Model
  Nakis, Nikolaos; Celikkanat, Abdulkadir; Boucherie, Louis; Djurhuus, Christian V; Burmester, Felix B; Mathias Holmelund, Daniel ; Frolcová, Monika; Mørup, Morten


• Algorithm for Constrained Markov Decision Process with Linear Convergence
  Gladin, Egor; Lavrik-Karmazin, Maksim ; Zainullina, Karina; Rudenko, Varvara; Gasnikov, Alexander; Takac, Martin


• Inducing Neural Collapse in Deep Long-tailed Learning
  LIU, Xuantong; Zhang, Jianfeng; Hu, Tianyang; CAO, He; Yao, Yuan; Pan, Lujia


• Encoding Domain Knowledge in Multi-view Latent Variable Models: A Bayesian Approach with Structured Sparsity
  Qoku, Arber; Buettner, Florian


• Regression as Classification: Influence of Task Formulation on Neural Network Features
  Stewart, Lawrence; Bach, Francis; Berthet, Quentin; Vert, Jean-Philippe


• Robust Linear Regression: Gradient-descent, Early-stopping, and Beyond
  Scetbon, Meyer; Dohmatob, Elvis


• Using Sliced Mutual Information to Study Memorization and Generalization in Deep Neural Networks
  Wongso, Shelvia; Ghosh, Rohan; Motani, Mehul


• Probing Graph Representations
  Akhondzadeh, Mohammad Sadegh; Lingam, Vijay; Bojchevski, Aleksandar


• Efficient SAGE Estimation via Causal Structure Learning
  Luther, Christoph; König, Gunnar; Grosse-Wentrup, Moritz