Olivier Teytaud

期刊論文

1. «Current frontiers in Computer-Go», Arpad Rimmel, Olivier Teytaud, Chang-Shing Lee, Shang-Rong Tsai, Mei-Hui Wang, Shi-Jim Yen. IEEE transactions on Computational Intelligence and Artificial Intelligence in Games, In Press (no ranking; recent journal).

2. «Intelligent Agents for the Game of Go », Jean-Baptiste Hoock, Chang-Shing Lee, Arpad Rimmel, Fabien Teytaud, Olivier Teytaud, Mei-Hui Wang, Computational Intelligence Magazine, In Press (general audience magazine; impact factor 2.62 according to “research gate”).

3. «Lower Bounds for Comparison Based Evolution Strategies using VC-dimension and Sign Patterns», Fournier, Hervé; Teytaud, Olivier, Algorithmica, (2009) springer. (« core » ranking A*)

4. «Continuous lunches are free plus the design of optimal optimization algorithms», Auger, Anne; Teytaud, Olivier, Algorithmica, (2009) springer. (« core » ranking A*)

5. «The Computational Intelligence of MoGo Revealed in Taiwan’s Computer Go Tournaments», Lee, Chang-Shing; Wang, Mei-Hui; Chaslot, Guillaume; Hoock, Jean-Baptiste; Rimmel, Arpad; Teytaud, Olivier; Tsai, Shang-Rong; Hsu, Shun-Chin; Hong, Tzung-Pei, IEEE Transactions on Computational Intelligence and AI in games, (2009) IEEE (no ranking; recent journal).

6. «Comparison-based algorithms are robust and randomized algorithms are anytime.», Gelly, Sylvain; Ruette, Sylvie; Teytaud, Olivier, Evolutionary Computation Journal, (2007) MIT Press (« core » ranking A).

7. «On the hardness of offline multiobjective optimization», Teytaud, Olivier, Evolutionary Computation Journal, (2007) MIT Press (« core » ranking A)

8. «Optimal estimation for Large-Eddy Simulation of turbulence and application to the analysis of subgrid models», Moreau, Antoine; Teytaud, Olivier; Bertoglio, Jean-Pierre, Physics of Fluids, (2006) 18 105101 (impact factor 1.213 according to bioscience.org)

9. «An adaptative filtering method to evalute normal vectors and surface areas of 3d objects. Application to snow images from X-ray tomography», Flin, Frédéric; Brzoska, Jean-Bruno; Coeurjolly, David; Pieritz, Romeu; Lesaffre, Bernard; Coléou, Cécile; Lamboley, Pascal; Teytaud, Olivier; Vignoles, Gérard; Delesse, Jean-François, IEEE Transactions on Image Processing, (2005) 14 5 585-596. (« core » ranking A*)

10. «Combiner connaissances expertes, hors-ligne, transientes et en ligne pour l’exploration Monte-Carlo», Chatriot, Louis; Fiter, Christophe; Chaslot, Guillaume; Gelly, Sylvain; Hoock, Jean-Baptiste; Perez, J.; Rimmel, Arpad; Teytaud, Olivier, Revue d’Intelligence Artificielle, (2008) Hermès.

11. «Bayesian Networks: a Non-Frequentist Approach for Parametrization, and a more Accurate Structural Complexity Measure», Gelly, Sylvain; Teytaud, Olivier, Revue d’Intelligence Artificielle, (2006) Hermes-Lavoisier.

12. «Universal Consistency and Bloat in GP», Gelly, Sylvain; Teytaud, Olivier; Bredeche, Nicolas; Schoenauer, Marc, Revue d’Intelligence Artificielle, (2006) Hermes-Lavoisier 

國際會議論文

1. «Complexity bounds for batch active learning in classification», P. Rolet, O. Teytaud, accepted for ECML 2010 (acceptance rate 25% en 2009; « core » ranking A)

2. «Scalability and Parallelization of Monte-Carlo Tree Search», A. Bourki, G. Chaslot, M. Coulm, V. Danjean, H. Doghmen, T. Hérault, J.-B. Hoock, A. Rimmel, F. Teytaud, O. Teytaud, P. Vayssière, Z. Yu, CG 2010 (no « core » ranking, but the main conference in games).

3. «Parameter Tuning by Simple Regret Algorithms and Multiple Simultaneous Hypothesis Testing», A. Bourki, M. Coulm, P. Rolet, O. Teytaud, P. Vayssière, ICINCO 2010.

4. «Log(lambda) modifications for optimal speed-up», F. Teytaud, O. Teytaud, PPSN 2010 (core ranking A).

5. «Continuous Upper Confidence Trees», A. Couëtoux, J.-B. Hoock, N. Sokolovska, accepted for LION 2010.

6. «On the Huge Benefit of Decisive Moves in Monte-Carlo Tree Search Algorithm», F. Teytaud, O. Teytaud, IEEE Conference on Computational Intelligence and Games 2010.

7. «Biasing Monte-Carlo simulations through RAVE Values», A. Rimmel, F. Teytaud, O. Teytaud, CG 2010.

8. «Handling Expensive Optimization with Large Noise», R. Coulom, P. Rolet, N. Sokolovska, O. Teytaud, Foga 2010 (Core ranking A+)

9. «A Principled Method for Exploiting Opening Books», R. Gaudel, J.-B. Hoock, N. Sokolovska, J. Pérez, O. Teytaud. CG 2010.

10. «Adaptive Noisy Optimization», Rolet P., Teytaud O. EvoStar 2010, Turquie (2010). (Springer, 56.2% d'acceptation en 2009)

11. «Bandit-Based Genetic Programming», Hoock J.-B., Teytaud O., 13th European Conference on Genetic Programming, Turquie (2010), short paper (50% acceptance in 2008).

12. «Consistency Modifications for Automatically Tuned Monte-Carlo Tree Search». Berthier V., Doghmen H., Teytaud O. Dans Lion4 - Lion4, Italie (2010). Springer LNCS.

13. «Bandit-based Estimation of Distribution Algorithms for Noisy Optimization» Rigorous Runtime Analysis, Rolet P., Teytaud O., Lion4, Italie (2010). Springer LNCS.

14. «Bias and variance in continuous EDA», Teytaud F., Teytaud O., EA 09, France (2009) (43% acceptance in 2007)

15. «Optimal Active Learning through Billiards and Upper Confidence Trees in Continous Domains», accepted for ECML 2009 (acceptance rate 25%; « core » ranking A)

16. «A Statistical Learning Perspective of Genetic Programming», Amil, Merve; Bredeche, Nicolas; Gagné, Christian; Gelly, Sylvain; Schoenauer, Marc; Teytaud, Olivier, (2009) Springer Proceedings of EuroGP 09 EuroGP. (poster / papier court; « core » ranking B)

17. «Grid coevolution for adaptive simulations; application to the building of opening books in the game of Go», Audouard, Pierre; Chaslot, Guillaume; Hoock, Jean-Baptiste; Rimmel, Arpad; Perez, J.; Teytaud, Olivier, (2009) Springer EvoGames LNCS. (66% d'acceptation)

18. «Adding expert knowledge and exploration in Monte-Carlo Tree Search», Chaslot, Guillaume; Fiter, Christophe; Hoock, Jean-Baptiste; Rimmel, Arpad; Teytaud, Olivier, (2009) Springer, LNCS, Advances in Computer Games (no « core » ranking, but the main conference in games).

19. «On the huge benefit of quasi-random mutations for multimodal optimization with application to grid-based tuning of neurocontrollers», Chaslot, Guillaume; Hoock, Jean-Baptiste; Teytaud, Fabien; Teytaud, Olivier, (2009) ESANN (« core » ranking B).

20. «A Novel Ontology for Computer Go Knowledge Management», Lee, Chang-Shing; Mei-Hui, Wang; Hong, Tzung-Pei; Chaslot, Guillaume; Hoock, Jean-Baptiste; Rimmel, Arpad; Teytaud, Olivier; Kuo, Yau-Hwang, (2009) IEEE FUZZ (« Core » Ranking A)

21. «Optimizing Low-Discrepancy Sequences with an Evolutionary Algorithm», Rainville, François-Michel De; Gagné, Christian; Teytaud, Olivier; Laurendeau, Denis, (2009) ACM 8 pages Genetic and Evolutionary Computation Conference. (« core » ranking A; best paper award in its track).

22. «Optimal robust expensive optimization is tractable», Rolet, Philippe; Sebag, Michele; Teytaud, Olivier, (2009) 8 pages Gecco 2009 (« core » ranking A).

23. «Creating an Upper-Confidence-Tree program for Havannah», Teytaud, Fabien; Teytaud, Olivier, (2009) ACG 12 , Springer LNCS (no « core » ranking, but the main conference in games).

24. «On the parallel speed-up of Estimation of Multivariate Normal Algorithm and Evolution Strategies», Teytaud, Fabien; Teytaud, Olivier, (2009) Springer Proceedings of EvoStar workshop 2009; EvoNum (evostar workshop, LNCS). (56.2% acceptance rate, nominated for Best Paper Award, 2nd)

25. «Why one must use reweighting in Estimation Of Distribution Algorithms», Teytaud, Fabien; Teytaud, Olivier, (2009) GECCO (« core » ranking A)

26. «On the Parallelization of Monte-Carlo planning», Gelly, Sylvain; Hoock, Jean-Baptiste; Rimmel, Arpad; Teytaud, Olivier; Kalemkarian, Yann, (2008) ICINCO. (acceptance rate 44.8 % in 2007)

27. «When does quasi-random work? », Teytaud, Olivier, (2008) Parallel Problem Solving from Nature (« core » ranking A, 42% d'acceptation)

28. «Lower bounds for evolution strategies using VC-dimension», Teytaud, Olivier; Fournier, Hervé, (2008) 10 pages Parallel Problem Solving from Nature (« core » ranking A, 42% d'acceptation)

29. «Continuous lunches are free!», Auger, Anne; Teytaud, Olivier, (2007) GECCO (core ranking A)

30.«DCMA, yet another derandomization in covariance-matrix-adaptation», Teytaud, Olivier; Gelly, Sylvain, (2007) GECCO (core ranking A)

31. «Conditionning, halting criteria and choosing lambda», Teytaud, Olivier, (2007) EA07, LNCS.

32. «Non linear programming for stochastic dynamic programming», Teytaud, Olivier; Gelly, Sylvain, (2007) Icinco 2007 (oral long). 11.9% acceptance rate for oral / long. Extended version in the book of selected papers: 22 papers out of 432 = 5% best papers.

33. «Active learning in regression, with an application to stochastic dynamic programming», Teytaud, Olivier; Gelly, Sylvain; Mary, Jérémie, (2007) ICINCO 2007 (44.8 % acceptance rate for oral/short paper).

34. «On the adaptation of the noise level for stochastic optimization», Teytaud, Olivier; Auger, Anne, (2007) IEEE Congress on Evolutionary Computation (« core » ranking A+)

35. «On the ultimate convergence rates for isotropic algorithms and the best choices among various forms of isotropy», Gelly, Sylvain; Mary, Jérémie; Teytaud, Olivier, (2006) Parallel Problem Solving from Nature (« core » ranking A, 55% d'acceptation)

36. «Learning for stochastic dynamic programming», Gelly, Sylvain; Mary, Jérémie; Teytaud, Olivier, (2006) 11th European Symposium on Artificial Neural Networks (ESANN) (« core » ranking B)

37. «Resource-Aware Parameterizations of EDA», Gelly, Sylvain; Teytaud, Olivier; Cagne, Christian, (2006) Congress on Evolutionary Computation (« core » ranking A+)

38. «Statistical inference and data mining: false discoveries control», Lallich, Stéphane; Teytaud, Olivier; Prudhomme, Elie, (2006) Compstat, Springer-Verlag 12 pages IASC.

39. «Why Simulation-Based Approachs with Combined Fitness are a Good Approach for Mining Spaces of Turing-equivalent Functions», Teytaud, Olivier, (2006) IEEE CEC 12 pages (« core » ranking A+)

40. «General lower bounds for evolutionary algorithms», Teytaud, Olivier; Gelly, Sylvain, (2006) Parallel Problem Solving from Nature (« core » ranking A, 55% d'acceptation)

41. «Local and global oder 3/2 convergence of a surrogate evolutionary algorithm», Auger, Anne; Schoenauer, Marc; Teytaud, Olivier, (2005) ACM Press Proceedings of the 2005 conference on Genetic and evolutionary computation 857-864 GECCO (« core » ranking A)

42. «A Statistical Learning Theory Approach of Bloat», Teytaud, Olivier; Gelly, Sylvain; Bredeche, Nicolas; Schoenauer, Marc, (2005) Genetic and Evolutionary Computation Conference 2005 (p427-428) Genetic and Evolutionary Computation Conference. (poster, « core » ranking A)

43. «Quasi-random mutations for evolution strategies», Teytaud, Olivier; Jebalia, Mohamed; Auger, Anne, (2005) Springer (Artificial Evolution) 12 pages LNCS.

44. «Convergence proofs, convergence rates and stopping criterions for multi-modal or multi-objective evolutionary algorithms», Bonnemay, Yann; Sebag, Michele; Teytaud, Olivier, (2005) 12 pages Evolution artificielle.

45. N. Tarrisson, M. Sebag, O. Teytaud, J. Lefevre, S. Baillet, Multi-objective Multimodal Optimization for mining Spatio-Temporal Patterns. Proceedings of IJCAI 2005 (core ranking A+).

國內會議論文

1. «Change Point Detection and Meta-Bandits for Online Learning in Dynamic Environments», Hartland, Cédric; Baskiotis, Nicolas; Gelly, Sylvain; Sebag, Michele; Teytaud, Olivier, CAp, (2007) cepadues 237-250 (25.8% d'acceptation en 2009)

2. «On the almost optimality of blind active sampling.», Teytaud, Olivier, (2008) CAP 2008 (25.8% d'acceptation en 2009)

3. «Inductive-deductive systems: a mathematical logic and statistical learning perspective», Baskiotis, Nicolas; Sebag, Michele; Teytaud, Olivier, (2007) CAP (25.8% d'acceptation en 2009)

4. «Upper Confidence Trees and Billiards for Optimal Active Learning», Rolet, Philippe; Sebag, Michèle; Teytaud, Olivier, (2009) CAP09 (25.8% d'acceptation)

5. «Anytime many-armed bandits», Teytaud, Olivier; Gelly, Sylvain; Sebag, Michele, (2007) CAP07 (25.8% d'acceptation en 2009)

6. «Apprentissage statistique et programmation génétique: la croissance du code est-elle inévitable ?», Gelly, Sylvain; Teytaud, Olivier; Bredeche, Nicolas; Schoenauer, Marc, (2005) 16 pages Conférence d’apprentissage CAP. (25.8% d'acceptation en 2009)

7. «Bayesian networks : a better than frequentist approach for parametrization, and a more accurate structural complexity measure than the number of parameters», Gelly, Sylvain; Teytaud, Olivier, (2005) 16 pages CAP (25.8% d'acceptation en 2009)