3 papers
stat.ML2026
A Finite-Sample Analysis of Quantile Temporal-Difference Learning
Zijie Cheng, Xiang Li, Yang Peng +1
Quantile temporal-difference learning (QTD) is an effective method for learning return distributions through quantile approximation, yet its finite-time behavior remains poorly und…
stat.ML2026
Online Inference for Quantile Distributional Reinforcement Learning
Zijie Cheng, Yang Peng, Zhihua Zhang
In this paper, we study online statistical inference for quantile-based distributional policy evaluation, which aims to characterize the distribution of discounted cumulative rewar…
stat.ML2026
Statistical Efficiency and Inference of Quantile Distributional Reinforcement Learning
Zijie Cheng, Yang Peng, Zhihua Zhang
In this paper, we study quantile-based distributional reinforcement learning from the perspective of statistical efficiency. We focus on distributional policy evaluation, whose goa…