Hao-Xu Chen — accepted AI-conference papers

2025

Federated Multi-armed Bandits with Efficient Bit-Level Communications

Haoran Zhang, Yang Xu, Xuchuang Wang, Hao-Xu Chen, Hao Qiu, Lin Yang +1

NeurIPS 2025poster

In this work, we study the federated multi-armed bandit (FMAB) problem, where a set of distributed agents collaboratively aim to minimize cumulative regret while interacting with a shared set of arms. Unlike traditional centralized bandit models, agents in FMAB settings are connected via a communica…

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2025

Near-Optimal Regret Bounds for Federated Multi-armed Bandits with Fully Distributed Communication

Haoran Zhang, Xuchuang Wang, Hao-Xu Chen, Hao Qiu, Lin Yang, Yang Gao

UAI 2025

In this paper, we focus on the research of federated multi-armed bandit (FMAB) problems where agents can only communicate with their neighbors. All agents aim to solve a common multi-armed bandit (MAB) problem to minimize individual regrets, while group regret can also be minimized. In a federated b

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