Web: http://arxiv.org/abs/2105.01648

May 11, 2022, 1:11 a.m. | Marc Aurel Vischer, Robert Tjarko Lange, Henning Sprekeler

cs.LG updates on arXiv.org arxiv.org

The lottery ticket hypothesis questions the role of overparameterization in
supervised deep learning. But how is the performance of winning lottery tickets
affected by the distributional shift inherent to reinforcement learning
problems? In this work, we address this question by comparing sparse agents who
have to address the non-stationarity of the exploration-exploitation problem
with supervised agents trained to imitate an expert. We show that feed-forward
networks trained with behavioural cloning compared to reinforcement learning
can be pruned to higher levels …

arxiv deep learning on reinforcement reinforcement learning

More from arxiv.org / cs.LG updates on arXiv.org

Data Analyst, Patagonia Action Works

@ Patagonia | Remote

Data & Insights Strategy & Innovation General Manager

@ Chevron Services Company, a division of Chevron U.S.A Inc. | Houston, TX

Faculty members in Research areas such as Bayesian and Spatial Statistics; Data Privacy and Security; AI/ML; NLP; Image and Video Data Analysis

@ Ahmedabad University | Ahmedabad, India

Director, Applied Mathematics & Computational Research Division

@ Lawrence Berkeley National Lab | Berkeley, Ca

Business Data Analyst

@ MainStreet Family Care | Birmingham, AL

Assistant/Associate Professor of the Practice in Business Analytics

@ Georgetown University McDonough School of Business | Washington DC