"multi-armed bandits" Papers
21 papers found
Conference
Breaking the $\log(1/\Delta_2)$ Barrier: Better Batched Best Arm Identification with Adaptive Grids
Tianyuan Jin, Qin Zhang, Dongruo Zhou
Constrained Feedback Learning for Non-Stationary Multi-Armed Bandits
Shaoang Li, Jian Li
Efficient Top-m Data Values Identification for Data Selection
Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng et al.
Evolution of Information in Interactive Decision Making: A Case Study for Multi-Armed Bandits
Yuzhou Gu, Yanjun Han, Jian Qian
Heterogeneous Multi-Agent Bandits with Parsimonious Hints
Amirmahdi Mirfakhar, Xuchuang Wang, Jinhang Zuo et al.
LASeR: Learning to Adaptively Select Reward Models with Multi-Arm Bandits
Duy Nguyen, Archiki Prasad, Elias Stengel-Eskin et al.
Learning Across the Gap: Hybrid Multi-armed Bandits with Heterogeneous Offline and Online Data
Qijia He, Minghan Wang, Xutong Liu et al.
On Speeding Up Language Model Evaluation
Jin Zhou, Christian Belardi, Ruihan Wu et al.
Pairwise Elimination with Instance-Dependent Guarantees for Bandits with Cost Subsidy
Ishank Juneja, Carlee Joe-Wong, Osman Yagan
Pareto Optimal Risk-Agnostic Distributional Bandits with Heavy-Tail Rewards
Kyungjae Lee, Dohyeong Kim, Taehyun Cho et al.
Revisiting Follow-the-Perturbed-Leader with Unbounded Perturbations in Bandit Problems
Jongyeong Lee, Junya Honda, Shinji Ito et al.
Satisficing Regret Minimization in Bandits
Qing Feng, Tianyi Ma, Ruihao Zhu
Tightening Regret Lower and Upper Bounds in Restless Rising Bandits
Cristiano Migali, Marco Mussi, Gianmarco Genalti et al.
uniINF: Best-of-Both-Worlds Algorithm for Parameter-Free Heavy-Tailed MABs
Yu Chen, Jiatai Huang, Yan Dai et al.
Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals
Ziyi Liu, Idan Attias, Daniel Roy
Communication-Efficient Collaborative Regret Minimization in Multi-Armed Bandits
Nikolai Karpov, Qin Zhang
Factored-Reward Bandits with Intermediate Observations
Marco Mussi, Simone Drago, Marcello Restelli et al.
Federated Combinatorial Multi-Agent Multi-Armed Bandits
Fares Fourati, Mohamed-Slim Alouini, Vaneet Aggarwal
Incentivized Learning in Principal-Agent Bandit Games
Antoine Scheid, Daniil Tiapkin, Etienne Boursier et al.
Leveraging (Biased) Information: Multi-armed Bandits with Offline Data
Wang Chi Cheung, Lixing Lyu
On Interpolating Experts and Multi-Armed Bandits
Houshuang Chen, Yuchen He, Chihao Zhang