75 - Reinforcement / Imitation Learning in NLP, with Hal Daumé III

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