Conferences, Machine Learning, Reinforcement

EWRL and NIPS 2016

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EWRL and NIPS 2016 I went to the European Workshop on Reinforcement Learning and NIPS last month and saw several interesting things. At EWRL, I particularly liked the talks from: Remi Munos on off-policy evaluation Mohammad Ghavamzadeh on learning safe policies Emma Brunskill on optimizing biased-but safe estimators (sense a theme?) Sergey Levine on low sample complexity applications of RL in robotics. My talk is here. Overall, this was a well organized workshop with diverse and interesting subjects, with the only caveat being that they had to limit registration At NIPS itself, I found the poster sessions fairly interesting. Allen-Zhu and Hazan had a new notion of a reduction (video). Zhao, Poupart, and Gordon had a new way to learn Sum-Product Networks Ho, Littman, MacGlashan, Cushman, and Austerwell, had a paper on how “Showing” is different from “Doing”. Toulis and…
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