Yizao Wang is co-author of the top level Go playing program Mogo, using Monte-Carlo Tree Search which uses patterns in the simulations and improvements in UCT[1].
Yizao Wang, Sylvain Gelly (2007). Modifications of UCT and Sequence-Like Simulations for Monte-Carlo Go. IEEE Symposium on Computational Intelligence and Games, Honolulu, USA, 2007, pdf
Yizao Wang, Jean-Yves Audibert and Rémi Munos (2008). Algorithms for Infinitely Many-Armed Bandits. Advances in Neural Information Processing Systems, pdf, Supplemental material - pdf
a Chinese mathematician and statistician, and assistant professor at Department of Mathematical Sciences, University of Cincinnati. He holds a B.Sc. in Mathematics from Peking University, Beijing, China, a M.Sc. in Applied Mathematics from École Polytechnique, Palaiseau, France, and Ph.D. in Statistics at University of Michigan, Ann Arbor, Michigan, United States in 2012. His research interests include Extreme value theory, sum- and max-stable processes and random fields, Central limit theorems for dependent sequences, Machine learning, bandit algorithms and applications to Computer-Go.
Yizao Wang is co-author of the top level Go playing program Mogo, using Monte-Carlo Tree Search which uses patterns in the simulations and improvements in UCT [1].
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