Aug. 4, 2022, 1:11 a.m. | Chengchun Shi, Jin Zhu, Ye Shen, Shikai Luo, Hongtu Zhu, Rui Song

cs.LG updates on arXiv.org arxiv.org

This paper is concerned with constructing a confidence interval for a target
policy's value offline based on a pre-collected observational data in infinite
horizon settings. Most of the existing works assume no unmeasured variables
exist that confound the observed actions. This assumption, however, is likely
to be violated in real applications such as healthcare and technological
industries. In this paper, we show that with some auxiliary variables that
mediate the effect of actions on the system dynamics, the target policy's …

arxiv confidence decision interval markov ml policy process

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne