5 papers · 1 filter
Online KL-Regularized Reinforcement Learning with Function Approximation under Misspecification
Haoyang Hong, Zichen Wang, Quanquan Gu +1
We study KL-regularized contextual bandits and episodic reinforcement learning (RL) under general function approximation with model misspecification. Existing guarantees rely on re…
Design-Based Bandits Under Network Interference: Trade-Off Between Regret and Statistical Inference
Zichen Wang, Haoyang Hong, Chuanhao Li +3
In multi-armed bandits with network interference (MABNI), the action taken by one node can influence the rewards of others, creating complex interdependence. While existing researc…
Provably Efficient Algorithm for Best Scoring Rule Identification in Online Principal-Agent Information Acquisition
Zichen Wang, Chuanhao Li, Huazheng Wang
We investigate the problem of identifying the optimal scoring rule within the principal-agent framework for online information acquisition problem. We focus on the principal's pers…
Online Experimental Design With Estimation-Regret Trade-off Under Network Interference
Zhiheng Zhang, Zichen Wang
Network interference has attracted significant attention in the field of causal inference, encapsulating various sociological behaviors where the treatment assigned to one individu…
Pure Exploration in Asynchronous Federated Bandits
Zichen Wang, Chuanhao Li, Chenyu Song +3
We study the federated pure exploration problem of multi-armed bandits and linear bandits, where agents cooperatively identify the best arm via communicating with the central s…