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Taylor-based pseudo-metrics for random process fitting in dynamic programming: expected loss minimization and risk management.

S. Gelly, J. Mary, and O. Teytaud. CAP, page 183-184. PUG, (2005)

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A Statistical Learning Perspective of Genetic Programming.N. Amil, N. Bredèche, C. Gagné, S. Gelly, M. Schoenauer, and O. Teytaud. EuroGP, volume 5481 of Lecture Notes in Computer Science, page 327-338. Springer, (2009)MULEX: Disentangling Exploitation from Exploration in Deep RL.L. Beyer, D. Vincent, O. Teboul, S. Gelly, M. Geist, and O. Pietquin. CoRR, (2019)Wasserstein Auto-Encoders.I. Tolstikhin, O. Bousquet, S. Gelly, and B. Schölkopf. CoRR, (2017)Achieving Master Level Play in 9 x 9 Computer Go.S. Gelly, and D. Silver. AAAI, page 1537-1540. AAAI Press, (2008)Resource-Aware Parameterizations of EDA.S. Gelly, O. Teytaud, and C. Gagné. IEEE Congress on Evolutionary Computation, page 2506-2512. IEEE, (2006)Monte-Carlo tree search and rapid action value estimation in computer Go.S. Gelly, and D. Silver. Artif. Intell., 175 (11): 1856-1875 (2011)Combiner connaissances expertes, hors-ligne, transientes et en ligne pour l'exploration Monte-Carlo. Apprentissage et MC.G. Chaslot, L. Chatriot, C. Fiter, S. Gelly, J. Hoock, J. Perez, A. Rimmel, and O. Teytaud. Rev. d'Intelligence Artif., 23 (2-3): 203-220 (2009)On the Ultimate Convergence Rates for Isotropic Algorithms and the Best Choices Among Various Forms of Isotropy.O. Teytaud, S. Gelly, and J. Mary. PPSN, volume 4193 of Lecture Notes in Computer Science, page 32-41. Springer, (2006)General Lower Bounds for Evolutionary Algorithms.O. Teytaud, and S. Gelly. PPSN, volume 4193 of Lecture Notes in Computer Science, page 21-31. Springer, (2006)Learning for stochastic dynamic programming.S. Gelly, J. Mary, and O. Teytaud. ESANN, page 191-196. (2006)

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Taylor-based pseudo-metrics for random process fitting in dynamic programming: expected loss minimization and risk management.

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PUMA

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Taylor-based pseudo-metrics for random process fitting in dynamic programming: expected loss minimization and risk management.

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Taylor-based pseudo-metrics for random process fitting in dynamic programming: expected loss minimization and risk management.