13 citations · 24 across the 4 of their papers we have counts for
4 papers
Adversarial Linear Contextual Bandits with Graph-Structured Side Observations
Lingda Wang, Bingcong Li, Huozhi Zhou +3
This paper studies the adversarial graphical contextual bandits, a variant of adversarial multi-armed bandits that leverage two categories of the most common side information: \emp…
Nonstationary Reinforcement Learning with Linear Function Approximation
Huozhi Zhou, Jinglin Chen, Lav R. Varshney +1
We consider reinforcement learning (RL) in episodic Markov decision processes (MDPs) with linear function approximation under drifting environment. Specifically, both the reward an…
Nearly Optimal Algorithms for Piecewise-Stationary Cascading Bandits
Lingda Wang, Huozhi Zhou, Bingcong Li +2
Cascading bandit (CB) is a popular model for web search and online advertising, where an agent aims to learn the most attractive items out of a ground set of size during th…
A Near-Optimal Change-Detection Based Algorithm for Piecewise-Stationary Combinatorial Semi-Bandits
Huozhi Zhou, Lingda Wang, Lav R. Varshney +1
We investigate the piecewise-stationary combinatorial semi-bandit problem. Compared to the original combinatorial semi-bandit problem, our setting assumes the reward distributions…