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75 - Reinforcement / Imitation Learning in NLP, with Hal Daumé III
NLP Highlights
English - November 21, 2018 17:53 - 43 minutes - 40.2 MB - ★★★★★ - 22 ratingsScience Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed
Previous Episode: 74 - Deep Reinforcement Learning Doesn't Work Yet, with Alex Irpan
In this episode, we invite Hal Daumé to continue the discussion on reinforcement learning, focusing on how it has been used in NLP. We discuss how to reduce NLP problems into the reinforcement learning framework, and circumstances where it may or may not be useful. We discuss imitation learning, roll-in and roll-out, and how to approximate an expert with a reference policy.
DAgger: https://www.semanticscholar.org/paper/A-Reduction-of-Imitation-Learning-and-Structured-to-Ross-Gordon/17eddf33b513ae1134abadab728bdbf6abab2a05?navId=citing-papers
RESLOPE: http://legacydirs.umiacs.umd.edu/~hal/docs/daume18reslope.pdf