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06/14/2023
Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources
Existing theoretical studies on offline reinforcement learning (RL) most...
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05/06/2023
On High-dimensional and Low-rank Tensor Bandits
Most existing studies on linear bandits focus on the one-dimensional cha...
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05/03/2023
Reward Teaching for Federated Multi-armed Bandits
Most of the existing federated multi-armed bandits (FMAB) designs are ba...
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10/27/2021
(Almost) Free Incentivized Exploration from Decentralized Learning Agents
Incentivized exploration in multi-armed bandits (MAB) has witnessed incr...
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10/27/2021
Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization
Despite the significant interests and many progresses in decentralized m...
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06/25/2021
Multi-player Multi-armed Bandits with Collision-Dependent Reward Distributions
We study a new stochastic multi-player multi-armed bandits (MP-MAB) prob...
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02/25/2021
Federated Multi-armed Bandits with Personalization
A general framework of personalized federated multi-armed bandits (PF-MA...
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01/28/2021
Federated Multi-Armed Bandits
Federated multi-armed bandits (FMAB) is a new bandit paradigm that paral...
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11/02/2020
On No-Sensing Adversarial Multi-player Multi-armed Bandits with Collision Communications
We study the notoriously difficult no-sensing adversarial multi-player m...
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02/29/2020