arXiv Machine Learning By Zijie Cheng, Xiang Li, Yang Peng, Zhihua Zhang

A Finite-Sample Analysis of Quantile Temporal-Difference Learning

Read the original on arXiv Machine Learning →

arXiv:2608. 27313v2 Announce Type: replace-cross Abstract: Quantile temporal-difference learning (QTD) is an effective method for learning return distributions through quantile approximation, yet its finite-time behavior remains poorly understood.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.