all AI news
On the Convergence of Policy in Unregularized Policy Mirror Descent. (arXiv:2205.08176v2 [math.OC] UPDATED)
May 20, 2022, 1:12 a.m. | Dachao Lin, Zhihua Zhang
cs.LG updates on arXiv.org arxiv.org
In this short note, we give the convergence analysis of the policy in the
recent famous policy mirror descent (PMD). We mainly consider the unregularized
setting following [11] with generalized Bregman divergence. The difference is
that we directly give the convergence rates of policy under generalized Bregman
divergence. Our results are inspired by the convergence of value function in
previous works and are an extension study of policy mirror descent. Though some
results have already appeared in previous work, we …
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Data Analyst (CPS-GfK)
@ GfK | Bucharest
Consultant Data Analytics IT Digital Impulse - H/F
@ Talan | Paris, France
Data Analyst
@ Experian | Mumbai, India
Data Scientist
@ Novo Nordisk | Princeton, NJ, US
Data Architect IV
@ Millennium Corporation | United States