← Search

John Lui

2 accepted papers

2022

Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms

NeurIPS 2022accept

In this paper, we study the combinatorial semi-bandits (CMAB) and focus on reducing the dependency of the batch-size $K$ in the regret bound, where $K$ is the total number of arms that can be pulled or triggered in each round. First, for the setting of CMAB with probabilistically triggered arms (CMA…

Cited by 23Source ↗PDF ↗Scholar ↗
2021

Cooperative Stochastic Bandits with Asynchronous Agents and Constrained Feedback

NeurIPS 2021poster

This paper studies a cooperative multi-armed bandit problem with $M$ agents cooperating together to solve the same instance of a $K$-armed stochastic bandit problem with the goal of maximizing the cumulative reward of agents. The agents are heterogeneous in (i) their limited access to a local subset…

Cited by 32Source ↗PDF ↗Scholar ↗