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45 documents ordered by : Date Title first author name document type Submit date

1 - 2 - 3

A new selection ratio for large population sizes Teytaud F. Evostar, Turquie (2010) [inria-00456335 - version 1]

Bandit-based Estimation of Distribution Algorithms for Noisy Optimization: Rigorous Runtime Analysis Rolet P., Teytaud O. Lion4, Italie (2010) [inria-00437140 - version 1]

Bias and variance in continuous EDA Teytaud F., Teytaud O. EA 09, France (2009) [inria-00451416 - version 1]

Discovering Linear Models of Grid Workload Elteto T., Germain-Renaud C., Bondon P. Rapport de recherche (2009) [inria-00435561 - version 1]

Boosting Active Learning to Optimality: a Tractable Monte-Carlo, Billiard-based Algorithm Rolet P., Sebag M., Teytaud O. ECML, Slovénie (2009) [inria-00433866 - version 1]

Adding expert knowledge and exploration in Monte-Carlo Tree Search Chaslot G., Fiter C., Hoock J.-B., Rimmel A., Teytaud O. Advances in Computer Games, Espagne (2009) [inria-00386477 - version 1]

A Novel Ontology for Computer Go Knowledge Management Lee C.-S., Mei-Hui W., Hong T.-P., Chaslot G., Hoock J.-B., Rimmel A., Teytaud O., Kuo Y.-H. IEEE FUZZ, Korea, Republic Of (2009) [inria-00386476 - version 1]

Optimizing Low-Discrepancy Sequences with an Evolutionary Algorithm Rainville F.-M. D., Gagné C., Teytaud O., Laurendeau D. Genetic and Evolutionary Computation Conference, Canada (2009) [inria-00386475 - version 1]

On the huge benefit of quasi-random mutations for multimodal optimization with application to grid-based tuning of neurocontrollers Chaslot G., Hoock J.-B., Teytaud F., Teytaud O. ESANN, Belgique (2009) [inria-00380125 - version 1]

Continuous lunches are free plus the design of optimal optimization algorithms Auger A., Teytaud O. Algorithmica (2009) [inria-00369788 - version 1]

The Computational Intelligence of MoGo Revealed in Taiwan's Computer Go Tournaments Lee C.-S., Wang M.-H., Chaslot G., Hoock J.-B., Rimmel A., Teytaud O., Tsai S.-R., Hsu S.-C., Hong T.-P. IEEE Transactions on Computational Intelligence and AI in games (2009) [inria-00369786 - version 1]

Grid coevolution for adaptive simulations; application to the building of opening books in the game of Go Audouard P., Chaslot G., Hoock J.-B., Rimmel A., Perez J., Teytaud O. EvoGames, Allemagne (2009) [inria-00369783 - version 1]

A Statistical Learning Perspective of Genetic Programming) Amil M., Bredeche N., Gagné C., Gelly S., Schoenauer M., Teytaud O. EuroGP, Allemagne (2009) [inria-00369782 - version 1]

On the parallel speed-up of Estimation of Multivariate Normal Algorithm and Evolution Strategies Teytaud F., Teytaud O. EvoNum (evostar workshop), Allemagne (2009) [inria-00369781 - version 1]

Why one must use reweighting in Estimation Of Distribution Algorithms Teytaud F., Teytaud O. GECCO, Canada (2009) [inria-00369780 - version 1]