1 citations · 1 across the 4 of their papers we have counts for
4 papers
Sample Complexity Characterization for Linear Contextual MDPs
Junze Deng, Yuan Cheng, Shaofeng Zou +1
Contextual Markov decision processes (CMDPs) describe a class of reinforcement learning problems in which the transition kernels and reward functions can change over time with diff…
Quickest Change Detection in Autoregressive Models
Zhongchang Sun, Shaofeng Zou
The problem of quickest change detection (QCD) in autoregressive (AR) models is investigated. A system is being monitored with sequentially observed samples. At some unknown time,…
Data-Driven Quickest Change Detection in (Hidden) Markov Models
Qi Zhang, Zhongchang Sun, Luis C. Herrera +1
The paper investigates the problems of quickest change detection in Markov models and hidden Markov models (HMMs). Sequential observations are taken from a (hidden) Markov model. A…
Provably Efficient Offline Reinforcement Learning with Trajectory-Wise Reward
Tengyu Xu, Yue Wang, Shaofeng Zou +1
The remarkable success of reinforcement learning (RL) heavily relies on observing the reward of every visited state-action pair. In many real world applications, however, an agent…