Papers
Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms
Xutong Liu, Jinhang Zuo, Siwei Wang et al.
Batch size-invariance for policy optimization
Jacob Hilton, Karl Cobbe, John Schulman
Bayesian Active Learning with Fully Bayesian Gaussian Processes
Christoffer Riis, Francisco Antunes, Frederik Hüttel et al.
Bayesian Clustering of Neural Spiking Activity Using a Mixture of Dynamic Poisson Factor Analyzers
Ganchao Wei, Ian H Stevenson, Xiaojing Wang
Bayesian inference via sparse Hamiltonian flows
Naitong Chen, Zuheng Xu, Trevor Campbell
Bayesian Optimistic Optimization: Optimistic Exploration for Model-based Reinforcement Learning
Chenyang Wu, Tianci Li, Zongzhang Zhang et al.
Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization
Samuel Daulton, Xingchen Wan, David Eriksson et al.
Bayesian Persuasion for Algorithmic Recourse
Keegan Harris, Valerie Chen, Joon Kim et al.
Bayesian Risk Markov Decision Processes
Yifan Lin, Yuxuan Ren, Enlu Zhou
Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics with Quantified Uncertainty
Luning Sun, Daniel Huang, Hao Sun et al.
BayesPCN: A Continually Learnable Predictive Coding Associative Memory
Jinsoo Yoo, Frank Wood
BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression
Haoyu Zhao, Boyue Li, Zhize Li et al.
Behavior Transformers: Cloning $k$ modes with one stone
Nur Muhammad Shafiullah, Zichen Cui, Ariuntuya (Arty) Altanzaya et al.
Bellman Residual Orthogonalization for Offline Reinforcement Learning
Andrea Zanette, Martin J Wainwright
Benchmarking and Analyzing 3D Human Pose and Shape Estimation Beyond Algorithms
Hui En Pang, Zhongang Cai, Lei Yang et al.
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability
Jonathan Crabbé, Alicia Curth, Ioana Bica et al.
Benchopt: Reproducible, efficient and collaborative optimization benchmarks
Thomas Moreau, Mathurin Massias, Alexandre Gramfort et al.
Benefits of Additive Noise in Composing Classes with Bounded Capacity
Alireza Fathollah Pour, Hassan Ashtiani
Benefits of Permutation-Equivariance in Auction Mechanisms
Tian Qin, Fengxiang He, Dingfeng Shi et al.
Benign Overfitting in Two-layer Convolutional Neural Networks
Yuan Cao, Zixiang Chen, Misha Belkin et al.
Benign, Tempered, or Catastrophic: Toward a Refined Taxonomy of Overfitting
Neil Mallinar, James Simon, Amirhesam Abedsoltan et al.
Benign Underfitting of Stochastic Gradient Descent
Tomer Koren, Roi Livni, Yishay Mansour et al.
Bessel Equivariant Networks for Inversion of Transmission Effects in Multi-Mode Optical Fibres
Joshua Mitton, Simon Mekhail, Miles Padgett et al.
Best of Both Worlds Model Selection
Aldo Pacchiano, Christoph Dann, Claudio Gentile
Better Best of Both Worlds Bounds for Bandits with Switching Costs
Idan Amir, Guy Azov, Tomer Koren et al.