Sylvain Gelly

	2009
20		Nur Merve Amil, Nicolas Bredeche, Christian Gagné, Sylvain Gelly, Marc Schoenauer, Olivier Teytaud: A Statistical Learning Perspective of Genetic Programming. EuroGP 2009: 327-338
	2008
19		Sylvain Gelly, David Silver: Achieving Master Level Play in 9 x 9 Computer Go. AAAI 2008: 1537-1540
18		Sylvain Gelly, Jean-Baptiste Hoock, Arpad Rimmel, Olivier Teytaud, Y. Kalemkarian: The Parallelization of Monte-Carlo Planning - Parallelization of MC-Planning. ICINCO-ICSO 2008: 244-249
	2007
17		Olivier Teytaud, Sylvain Gelly: DCMA: yet another derandomization in covariance-matrix-adaptation. GECCO 2007: 955-963
16		Olivier Teytaud, Sylvain Gelly, Jérémie Mary: Active learning in regression, with application to stochastic dynamic programming. ICINCO-ICSO 2007: 198-205
15		Olivier Teytaud, Sylvain Gelly: Nonlinear programming in approximate dynamic programming - bang-bang solutions, stock-management and unsmooth penalties. ICINCO-ICSO 2007: 47-54
14		Sylvain Gelly, David Silver: Combining online and offline knowledge in UCT. ICML 2007: 273-280
13		Sylvain Gelly, Sylvie Ruette, Olivier Teytaud: Comparison-Based Algorithms Are Robust and Randomized Algorithms Are Anytime. Evolutionary Computation 15(4): 411-434 (2007)
	2006
12		Sylvain Gelly, Jérémie Mary, Olivier Teytaud: Learning for stochastic dynamic programming. ESANN 2006: 191-196
11		Olivier Teytaud, Sylvain Gelly: General Lower Bounds for Evolutionary Algorithms. PPSN 2006: 21-31
10		Olivier Teytaud, Sylvain Gelly, Jérémie Mary: On the Ultimate Convergence Rates for Isotropic Algorithms and the Best Choices Among Various Forms of Isotropy. PPSN 2006: 32-41
9		Sylvain Gelly, Olivier Teytaud: Bayesian Networks: a Non-Frequentist Approach for Parametrization, and a more Accurate Structural Complexity Measure Bayesian Networks Learning. Revue d'Intelligence Artificielle 20(6): 717-755 (2006)
8		Sylvain Gelly, Olivier Teytaud, Nicolas Bredeche, Marc Schoenauer: Universal Consistency and Bloat in GP Some theoretical considerations about Genetic Programming from a Statistical Learning Theory viewpoint. Revue d'Intelligence Artificielle 20(6): 805-827 (2006)
	2005
7		Sylvain Gelly, Nicolas Bredeche, Michèle Sebag: HMM hiérarchiques et factorisés: mécanisme d'inférence et apprentissage à partir de peu de données. CAP 2005: 143-144
6		Sylvain Gelly, Olivier Teytaud: Statistical asymptotic and non-asymptotic consistency of bayesian networks: convergence to the right structure and consistent probability estimates. CAP 2005: 147-162
5		Sylvain Gelly, Olivier Teytaud, Nicolas Bredeche, Marc Schoenauer: Apprentissage statistique et programmation génétique: la croissance du code est-elle inévitable? CAP 2005: 163-178
4		Sylvain Gelly, Jérémie Mary, Olivier Teytaud: Taylor-based pseudo-metrics for random process fitting in dynamic programming: expected loss minimization and risk management. CAP 2005: 183-184
3		Sylvain Gelly, Olivier Teytaud, Nicolas Bredeche, Marc Schoenauer: A statistical learning theory approach of bloat. GECCO 2005: 1783-1784
2		Sylvain Gelly, Nicolas Bredeche, Michèle Sebag: From Factorial and Hierarchical HMM to Bayesian Network: A Representation Change Algorithm. SARA 2005: 107-120
1		Yann Semet, Sylvain Gelly, Marc Schoenauer, Michèle Sebag: Artificial Agents and Speculative Bubbles CoRR abs/cs/0511093: (2005)

Coauthor Index

1	Nur Merve Amil	[20]
2	Nicolas Bredeche	[2] [3] [5] [7] [8] [20]
3	Christian Gagné	[20]
4	Jean-Baptiste Hoock	[18]
5	Y. Kalemkarian	[18]
6	Jérémie Mary	[4] [10] [12] [16]
7	Arpad Rimmel	[18]
8	Sylvie Ruette	[13]
9	Marc Schoenauer	[1] [3] [5] [8] [20]
10	Michèle Sebag	[1] [2] [7]
11	Yann Semet	[1]
12	David Silver	[14] [19]
13	Olivier Teytaud	[3] [4] [5] [6] [8] [9] [10] [11] [12] [13] [15] [16] [17] [18] [20]

Colors in the list of coauthors