9 citations · 9 across the 2 of their papers we have counts for
3 papers
cs.LG2022
Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian
Paria Rashidinejad, Hanlin Zhu, Kunhe Yang +2
Offline reinforcement learning (RL), which refers to decision-making from a previously-collected dataset of interactions, has received significant attention over the past years. Mu…
cs.PF2021★ 9 cited
Nudge: Stochastically Improving upon FCFS
Isaac Grosof, Kunhe Yang, Ziv Scully +1
The First-Come First-Served (FCFS) scheduling policy is the most popular scheduling algorithm used in practice. Furthermore, its usage is theoretically validated: for light-tailed…
cs.LG2020
-learning with Logarithmic Regret
Kunhe Yang, Lin F. Yang, Simon S. Du
This paper presents the first non-asymptotic result showing that a model-free algorithm can achieve a logarithmic cumulative regret for episodic tabular reinforcement learning if t…