Author

William Chang

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#machine learning Preprint Sep 2026

Provably Efficient Reinforcement Learning in Continuous-Time Episodic MDPs with Poisson Decision Epochs

Many real-world reinforcement learning (RL) problems evolve in continuous time, where decisions occur at irregular, event-driven intervals rather than at fixed discrete steps. We study episodic continuous-time Markov Decision Processes (MDPs) in which decision epochs are governed by a homogeneous Poisson process and th...

Kenny Guo, Valentio Iverson, Sahan Wijetunga et al. · 0 citations

Preprint Aug 2026

DCM Bandits: Multiplayer Information Asymmetric Cascading Bandits for Multiple Clicks

In this work, we extend the Dependent Click Model (DCM) Bandits to a multiplayer information-asymmetric setting, where multiple agents interact with a shared ranked list and may observe multiple clicks per session, introducing new challenges for selection strategies. We study asymmetry in (1) actions and (2) rewards, p...

Andy Wang, Charlton Shih, William Chang · 0 citations

Preprint Aug 2026

The Price of Decentralization in Top-$K$ Arm Identification

Cooperative teams often need to agree on the best few options rather than simply accumulate reward, and they must do so while each member sees only a fragment of the team's collective experience. We study this as top-$K$ joint-arm identification in multi-agent multi-armed bandits: at every round $M$ agents simultaneous...

Larissa Xu, Jasmine Nguyen, William Chang · 0 citations