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Fabien TEYTAUD

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Fabien TEYTAUD

Guided-Generative Network: A New Robust Deep Learning Architecture for Noise Characterization in Monte-Carlo Rendering

Jérôme Buisine, Fabien Teytaud, Samuel Delepoulle, Christophe Renaud. Guided-Generative Network: A New Robust Deep Learning Architecture for Noise Characterization in Monte-Carlo Rendering. Deep Learning Applications, Volume 4, Springer, pp.293-315, 2022, Advances in Intelligent Systems and Computing, book séries (AISC,1434), 9789811961526. ⟨10.1007/978-981-19-6153-3_12⟩. ⟨hal-03875168⟩

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Improving Nevergrad's Algorithm Selection Wizard NGOpt through Automated Algorithm Configuration

Risto Trajanov, Ana Nikolikj, Gjorgjina Cenikj, Fabien Teytaud, Mathurin Videau, et al.. Improving Nevergrad's Algorithm Selection Wizard NGOpt through Automated Algorithm Configuration. 17th Proceedings of Parallel Problem Solving from Nature - (PPSN) 2022, Sep 2022, Dortmund, Germany. pp.18-31, ⟨10.1007/978-3-031-14714-2_2⟩. ⟨hal-03740762⟩

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Guided-Generative Network for noise detection in Monte-Carlo rendering

Jérôme Buisine, Fabien Teytaud, Samuel Delepoulle, Christophe Renaud. Guided-Generative Network for noise detection in Monte-Carlo rendering. 20th IEEE International Conference On Machine Learning And Applications, Dec 2021, Pasadena, United States. ⟨hal-03374214⟩

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Many-Objective Optimization for Diverse Image Generation

Nathanaël Carraz Rakotonirina, Andry Rasoanaivo, Laurent Najman, Petr Kungurtsev, Jeremy Rapin, et al.. Many-Objective Optimization for Diverse Image Generation. 2021. ⟨hal-03425742⟩

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Upper Confidence Tree for planning restart strategies in Multi-Modal Optimization

Amaury Dubois, Julien Dehos, Fabien Teytaud. Upper Confidence Tree for planning restart strategies in Multi-Modal Optimization. Soft Computing, 2021, 25 (2), pp.1007-1015. ⟨10.1007/s00500-020-05196-w⟩. ⟨hal-02951196⟩

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Short term soil moisture forecasts for potato crop farming: a machine learning approach

Amaury Dubois, Fabien Teytaud, Sébastien Verel. Short term soil moisture forecasts for potato crop farming: a machine learning approach. Computers and Electronics in Agriculture, In press, 180, ⟨10.1016/j.compag.2020.105902⟩. ⟨hal-03081945⟩

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EvolGAN: Evolutionary Generative Adversarial Networks

Baptiste Rozière, Fabien Teytaud, Vlad Hosu, Hanhe Lin, Jeremy Rapin, et al.. EvolGAN: Evolutionary Generative Adversarial Networks. 15th Asian Conference on Computer Vision (ACCV), Nov 2020, Virtual, Japan. ⟨hal-03091443⟩

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Fully Parallel Hyperparameter Search: Reshaped Space-Filling

M.-L Cauwet, C Couprie, Julien Dehos, P Luc, J Rapin, et al.. Fully Parallel Hyperparameter Search: Reshaped Space-Filling. 37th International Conference on Machine Learning (ICML), Jul 2020, Virtual Event, France. ⟨hal-03091435⟩

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BCMA-ES: A Bayesian approach to CMA-ES

Eric Benhamou, David Saltiel, Sébastien Verel, Fabien Teytaud. BCMA-ES: A Bayesian approach to CMA-ES. GECCO 2020 - The Genetic and Evolutionary Computation Conference, Jul 2020, ONLINE, Mexico. ⟨hal-02886512⟩

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Bayesian CMA-ES: a new approach

Eric Benhamou, David Saltiel, Sébastien Verel, Fabien Teytaud. Bayesian CMA-ES: a new approach. GECCO '20: Genetic and Evolutionary Computation Conference, Jul 2020, Cancún, Mexico. pp.203-204, ⟨10.1145/3377929.3389913⟩. ⟨hal-03814858⟩

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Versatile black-box optimization

Jialin Liu, Antoine Moreau, Mike Preuss, Jeremy Rapin, Baptiste Roziere, et al.. Versatile black-box optimization. GECCO '20: Genetic and Evolutionary Computation Conference, Jul 2020, Cancún Mexico, France. pp.620-628, ⟨10.1145/3377930.3389838⟩. ⟨hal-03049284⟩

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Polygames: Improved Zero Learning

Tristan Cazenave, Yen-Chi Chen, Guan-Wei Chen, Shi-Yu Chen, Xian-Dong Chiu, et al.. Polygames: Improved Zero Learning. International Computer Games Association Journal, 2020, 42 (4), pp.244-256. ⟨hal-03117499⟩

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Automatic calibration of a farm irrigation model: a multi-modal optimization approach

Amaury Dubois, Fabien Teytaud, Eric Ramat, Sébastien Verel. Automatic calibration of a farm irrigation model: a multi-modal optimization approach. EA2019 Artificial Evolution, Oct 2019, Mulhouse, France. ⟨hal-02406612⟩

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Improving Multi-Modal Optimization Restart Strategy Through Multi-Armed Bandit

Amaury Dubois, Julien Dehos, Fabien Teytaud. Improving Multi-Modal Optimization Restart Strategy Through Multi-Armed Bandit. IEEE ICMLA 2018 : 17th IEEE International Conference On Machine Learning And Applications, Dec 2018, orlando, United States. ⟨hal-02014193⟩

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Generating Term Weighting Schemes through Genetic Programming

Ahmad Mazyad, Fabien Teytaud, Cyril Fonlupt. Generating Term Weighting Schemes through Genetic Programming. The 4th Annual Conference on machine Learning, Optimization and Data science (LOD), Sep 2018, Tuscany, Italy. pp.92-103. ⟨hal-01859657⟩

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Information Gain Based Term Weighting Method for Multi-label Text Classification Task

Ahmad Mazyad, Fabien Teytaud, Cyril Fonlupt. Information Gain Based Term Weighting Method for Multi-label Text Classification Task. Intelligent Systems Conference (IntelliSys) 2018, Sep 2018, London, United Kingdom. ⟨hal-01859697⟩

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Generating Term Weighting Schemes through Genetic Programming

Ahmad Mazyad, Fabien Teytaud, Cyril Fonlupt. Generating Term Weighting Schemes through Genetic Programming. GECCO 2018, the Genetic and Evolutionary Computation Conference Companion a recombination of the 27th International Conference on Genetic Algorithms (ICGA) and the 23rd Annual Genetic Programming Conference (GP), Jul 2018, Kyoto, Japan. pp.268-269. ⟨hal-01859681⟩

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Multi-armed bandit for stratified sampling: Application to numerical integration

Florian Leprêtre, Fabien Teytaud, Julien Dehos. Multi-armed bandit for stratified sampling: Application to numerical integration. TAAI 2017 - Conference on Technologies and Applications of Artificial Intelligence, Dec 2017, Taipei, Taiwan. pp.190-195, ⟨10.1109/TAAI.2017.34⟩. ⟨hal-01660617⟩

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Learning new Term Weighting Schemes with Genetic Programming

Ahmad Mazyad, Fabien Teytaud, Cyril Fonlupt. Learning new Term Weighting Schemes with Genetic Programming. The Biennial International Conference on Artificial Evolution, Oct 2017, Paris, France. 2017. ⟨hal-01662138⟩

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A Comparative Study on Term Weighting Schemes for Text Classification

Ahmad Mazyad, Fabien Teytaud, Cyril Fonlupt. A Comparative Study on Term Weighting Schemes for Text Classification. The Third International Conference on Machine Learning, Optimization and Big Data, Sep 2017, Volterra, Italy. pp.100-108. ⟨hal-01662131⟩

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Learning opening books in partially observable games: using random seeds in Phantom Go

Tristan Cazenave, Jialin Liu, Fabien Teytaud, Olivier Teytaud. Learning opening books in partially observable games: using random seeds in Phantom Go. CIG 2016 - Computer intelligence and Games, Sep 2016, Santorini, Greece. ⟨hal-01413229⟩

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QR mutations improve many evolution strategies -a lot on highly multimodal problems

Fabien Teytaud, Olivier Teytaud. QR mutations improve many evolution strategies -a lot on highly multimodal problems. ACM-GECCO'16, Jul 2016, Denver, United States. pp.35-36, ⟨10.1145/1235⟩. ⟨hal-01406727⟩

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Pruning playouts in Monte-Carlo Tree Search for the game of Havannah

Joris Duguépéroux, Ahmad Mazyad, Fabien Teytaud, Julien Dehos. Pruning playouts in Monte-Carlo Tree Search for the game of Havannah. The 9th International Conference on Computers and Games (CG2016), Jun 2016, Leiden, Netherlands. ⟨hal-01342347⟩

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On the tactical and strategic behaviour of MCTS when biasing random simulations

Fabien Teytaud, Julien Dehos. On the tactical and strategic behaviour of MCTS when biasing random simulations. International Computer Games Association Journal, 2015, 38 (2), pp.67-80. ⟨hal-01267056⟩

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Differential evolution for strongly noisy optimization: Use 1.01n resamplings at iteration n and reach the − 1/2 slope

Shih-Yuan Chiu, Ching-Nung Lin, Jialin Liu, Tsang-Cheng Su, Fabien Teytaud, et al.. Differential evolution for strongly noisy optimization: Use 1.01n resamplings at iteration n and reach the − 1/2 slope. 2015 IEEE Congress on Evolutionary Computation (IEEE CEC 2015), May 2015, Sendai, Japan. pp.338 - 345, ⟨10.1109/CEC.2015.7256911⟩. ⟨hal-01245526⟩

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Differential Evolution for Strongly Noisy Optimization: Use 1.01$^n$ Resamplings at Iteration n and Reach the -1/2 Slope

Shih-Yuan Chiu, Ching-Nung Lin, Jialin Liu, Tsang-Cheng Su, Fabien Teytaud, et al.. Differential Evolution for Strongly Noisy Optimization: Use 1.01$^n$ Resamplings at Iteration n and Reach the -1/2 Slope. 2015 IEEE Congress on Evolutionary Computation (IEEE CEC), May 2015, Sendai, Japan. ⟨hal-01120892⟩

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Parallel Evolutionary Algorithms Performing Pairwise Comparisons

Marie-Liesse Cauwet, Olivier Teytaud, Shih-Yuan Chiu, Kuo-Min Lin, Shi-Jim Yen, et al.. Parallel Evolutionary Algorithms Performing Pairwise Comparisons. Foundations of Genetic Algorithms, 2015, Aberythswyth, United Kingdom. pp.99-113. ⟨hal-01077626⟩

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Monte-Carlo Tree Search for the “Mr Jack” Board Game

Ahmad Mazyad, Fabien Teytaud, Cyril Fonlupt. Monte-Carlo Tree Search for the “Mr Jack” Board Game. International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI), 2015. ⟨hal-01406506⟩

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Monte-Carlo Tree Search for the Game of "7 Wonders

Denis Robilliard, Cyril Fonlupt, Fabien Teytaud. Monte-Carlo Tree Search for the Game of "7 Wonders". European Conference in Artificial Intelligence (ECAI), Aug 2014, Prague, Czech Republic. pp.64 - 77, ⟨10.1007/978-3-319-14923-3_5⟩. ⟨hal-01406496⟩

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A Survey of Meta-Heuristics used for Computing Maximin Latin Hypercube

Arpad Rimmel, Fabien Teytaud. A Survey of Meta-Heuristics used for Computing Maximin Latin Hypercube. EvoCOP 2014, Apr 2014, Grenade, Spain. 12 p. ⟨hal-00926729⟩

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