58 citations · 169 across the 25 of their papers we have counts for
5 papers · 1 filter
Efficient Online Learning with Offline Datasets for Infinite Horizon MDPs: A Bayesian Approach
Dengwang Tang, Rahul Jain, Botao Hao +1
In this paper, we study the problem of efficient online reinforcement learning in the infinite horizon setting when there is an offline dataset to start with. We assume that the of…
Sequential Best-Arm Identification with Application to Brain-Computer Interface
Xin Zhou, Botao Hao, Jian Kang +2
A brain-computer interface (BCI) is a technology that enables direct communication between the brain and an external device or computer system. It allows individuals to interact wi…
Bridging Imitation and Online Reinforcement Learning: An Optimistic Tale
Botao Hao, Rahul Jain, Dengwang Tang +1
In this paper, we address the following problem: Given an offline demonstration dataset from an imperfect expert, what is the best way to leverage it to bootstrap online learning p…
Leveraging Demonstrations to Improve Online Learning: Quality Matters
Botao Hao, Rahul Jain, Tor Lattimore +2
We investigate the extent to which offline demonstration data can improve online learning. It is natural to expect some improvement, but the question is how, and by how much? We sh…
Sample Efficient Deep Reinforcement Learning via Local Planning
Dong Yin, Sridhar Thiagarajan, Nevena Lazic +3
The focus of this work is sample-efficient deep reinforcement learning (RL) with a simulator. One useful property of simulators is that it is typically easy to reset the environmen…