Zobrazeno 1 - 10
of 2 292
pro vyhledávání: '"Bennett, Andrew"'
We study the evaluation of a policy under best- and worst-case perturbations to a Markov decision process (MDP), using transition observations from the original MDP, whether they are generated under the same or a different policy. This is an importan
Externí odkaz:
http://arxiv.org/abs/2404.00099
Autor:
Bruno, Barbara C., Cackowski, Celia, Frederick, John Adam, Vincent, Robert, Bennett, Andrew, Böttjer-Wilson, Daniela, Engels, Jennifer, Flight, Chris, Lang, Amy, Lawrence, Lisa Ayers, Smith, Bethany, Takacs, Jacqueline
Publikováno v:
Oceanography, 2024 Mar 01. 37(1), 54-59.
Externí odkaz:
https://www.jstor.org/stable/27301084
Publikováno v:
PMLR, Volume 238, 2024
Low-Rank Markov Decision Processes (MDPs) have recently emerged as a promising framework within the domain of reinforcement learning (RL), as they allow for provably approximately correct (PAC) learning guarantees while also incorporating ML algorith
Externí odkaz:
http://arxiv.org/abs/2311.03564
Autor:
Bennett, Andrew, Kallus, Nathan, Mao, Xiaojie, Newey, Whitney, Syrgkanis, Vasilis, Uehara, Masatoshi
We consider estimation of parameters defined as linear functionals of solutions to linear inverse problems. Any such parameter admits a doubly robust representation that depends on the solution to a dual linear inverse problem, where the dual solutio
Externí odkaz:
http://arxiv.org/abs/2307.13793
Autor:
Bennett, Andrew, Kallus, Nathan, Mao, Xiaojie, Newey, Whitney, Syrgkanis, Vasilis, Uehara, Masatoshi
In this paper, we study nonparametric estimation of instrumental variable (IV) regressions. Recently, many flexible machine learning methods have been developed for instrumental variable estimation. However, these methods have at least one of the fol
Externí odkaz:
http://arxiv.org/abs/2302.05404