Difference between revisions of "Sylvain Gelly"
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Revision as of 23:40, 28 November 2018
Sylvain Gelly [1]
Sylvain Gelly,
a French computer scientist, deep learning researcher at Google Brain Zurich [2], and former member of the Learning and Optimisation Group (A&O) [3] in the Laboratoire de recherche en informatique (LRI) under the direction of Michèle Sebag and Nicolas Bredèche at Paris-Sud 11 University. He defended his Ph.D. thesis A Contribution to Reinforcement Learning; Application to Computer Go in 2007 [4]. His research interests covers machine learning and he is one of the authors of OpenDP [5], a general and featured framework of reinforcement learning, and in particular of dynamic programming, and co-authored the top level Go playing program Mogo, using Monte-Carlo Tree Search which uses patterns in the simulations and improvements in UCT [6][7].
Selected Publications
2005 ...
- Sylvain Gelly, Nicolas Bredèche, Michèle Sebag (2005). From Factorial and Hierarchical HMM to Bayesian Network : A Representation Change Algorithm. Proceedings of the Symposium on Abstraction, Reformulation and Approximation 2005, p107-120 (SARA 2005). Reprinted in Lecture Notes in Computer Science, Vol. 3607
2006
- Sylvain Gelly, Olivier Teytaud, Nicolas Bredèche, Marc Schoenauer (2006). Universal Consistency and Bloat in GP. Some theoretical considerations about Genetic Programming from a Statistical Learning Theory viewpoint. pdf (draft)
- Sylvain Gelly, Olivier Teytaud (2006). Bayesian networks : a better than frequentist approach for parametrization, and a more accurate structural complexity measure than the number of parameters. pdf (draft)
- Sylvain Gelly, Jérémie Mary, Olivier Teytaud (2006). Learning for stochastic dynamic programming. pdf
- Sylvain Gelly, Jérémie Mary, Olivier Teytaud (2006). On the ultimate convergence rates for isotropic algorithms and the best choices among various forms of isotropy. PPSN, 2006, pdf
- Olivier Teytaud, Sylvain Gelly (2006). General lower bounds for evolutionary algorithms. pdf
- Sylvain Gelly, Yizao Wang (2006). Exploration exploitation in Go: UCT for Monte-Carlo Go. pdf
- Sylvain Gelly, Yizao Wang, Rémi Munos, Olivier Teytaud (2006). Modification of UCT with Patterns in Monte-Carlo Go. INRIA
2007
- 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
- Sylvain Gelly, Yizao Wang (2007). MoGo wins 19x19 Go tournament. ICGA Journal, Vol. 30, No. 2 » 12th Computer Olympiad
- Sylvain Gelly (2007). A Contribution to Reinforcement Learning; Application to Computer Go. Ph.D. thesis, pdf
- Sylvain Gelly, David Silver (2007). Combining Online and Offline Knowledge in UCT. pdf
- Sylvain Gelly, Olivier Teytaud, Jérémie Mary (2007). Active learning in regression, with application to stochastic dynamic programming. ICINCO and CAP, 2007, pdf
2008
- Sylvain Gelly, David Silver (2008). Achieving Master Level Play in 9 x 9 Computer Go. pdf
- Guillaume Chaslot, Louis Chatriot, Christophe Fiter, Sylvain Gelly, Jean-Baptiste Hoock, Julien Pérez, Arpad Rimmel, Olivier Teytaud (2008). Combining expert, offline, transient and online knowledge in Monte-Carlo exploration. pdf
- Sylvain Gelly, Jean-Baptiste Hoock, Arpad Rimmel, Olivier Teytaud, Yann Kalemkarian (2008). The Parallelization of Monte-Carlo Planning - Parallelization of MC-Planning. ICINCO-ICSO 2008: 244-249, pdf, slides as pdf
2009
- Nur Merve Amil, Nicolas Bredèche, Christian Gagné, Sylvain Gelly, Marc Schoenauer, Olivier Teytaud (2009). A Statistical Learning Perspective of Genetic Programming. EuroGP 2009, pdf
- Vincent Berthier, Amine Bourki, Matthieu Coulm, Guillaume Chaslot, Christophe Fiter, Sylvain Gelly, Jean-Baptiste Hoock, Rémi Munos, Julien Pérez, Arpad Rimmel, Philippe Rolet, Olivier Teytaud, Paul Vayssière, Yizao Wang, Ziqin Yu (et al.) (2009). Computer-Go is not only for Go. Korea, August 2009 slides as pdf
2010 ...
- Sylvain Gelly, David Silver (2011). Monte-Carlo tree search and rapid action value estimation in computer Go. Artificial Intelligence, Vol. 175, No. 11
- Sylvain Gelly, Marc Schoenauer, Michèle Sebag, Olivier Teytaud, Levente Kocsis, David Silver, Csaba Szepesvári (2012). The Grand Challenge of Computer Go: Monte Carlo Tree Search and Extensions. Communications of the ACM, Vol. 55, No. 3, pdf preprint
- Sylvain Gelly, Karol Kurach, Marcin Michalski, Xiaohua Zhai (2018). MemGEN: Memory is All You Need. arXiv:1803.11203 [9]
External Links
- Sylvain Gelly | LinkedIn
- Sylvain Gelly - Google Scholar Citations
- Sylvain Gelly's ICGA Tournaments
- Gelly, Sylvain from computer-go.info
- Computer Olympiad 2007, Interview with Silvian Gelly by Harry Weerheijm, EuroGoTV, YouTube Video
References
- ↑ Capture from the 12th Computer Olympiad Video interview
- ↑ Sylvain Gelly | LinkedIn
- ↑ Laboratoire de Recherche en Informatique - A&O Group
- ↑ Sylvain Gelly (2007). A Contribution to Reinforcement Learning; Application to Computer Go. Ph.D. thesis, pdf
- ↑ Sylvain Gelly's Home Page - OpenDP, a free stochastic dynamic programming tool for stochastic dynamic programming.
- ↑ Sylvain Gelly's home page - MoGo
- ↑ MoGo: a software for the Game of Go
- ↑ dblp: Sylvain Gelly
- ↑ April 01, 2018
