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When game theory meets machine learning
Date: 2017/7/13             Browse: 221
Speaker:   Prof. Tao Qin
Time:        July 13,1:00 pm-2:30 pm.

Location:  Room 1A-200  , SIST Building

Inviter:   Prof. Dengji Zhao


Machine learning aims at learning from data, while game theory studies conflict and cooperation between intelligent rational decision-makers. In recent years, learning systems have been formulated as games and conventional single-agent learning has been extended to multi-agent learning; game theory has been powered by machine learning techniques and games have been better analyzed and designed by leveraging data. In this talk, I will briefly introduce our recent work about the interaction between game theory and machine learning, including dual learning, generative adversarial networks, etc.



                                                                                                                  SIST-Seminar 17037