Segmentation and Length Estimation of 3D Discrete Curves. - David Coeurjolly; Isabelle Debled-Rennesson; Olivier Teytaud (Digital and Image Geometry, 2000)

Identification de la langue et catégorisation de textes basées sur les N-grammes. - Radwan Jalam; Olivier Teytaud (EGC, 2001)

Bounds on the Generalization Ability of Bayesian Inference and Gibbs Algorithms. - Olivier Teytaud; Hélène Paugam-Moisy (ICANN, 2001)

Kernel Based Image Classification. - Olivier Teytaud; David Sarrut (ICANN, 2001)

Decidability of the halting problem for Matiyasevich deterministic machines. - Olivier Teytaud (Theor. Comput. Sci., 2001)

Lower Bounds for Training and Leave-One-Out Estimates of the Generalization Error. - Gérald Gavin; Olivier Teytaud (ICANN, 2002)

Multigrid Convergence and Surface Area Estimation. - David Coeurjolly; Frédéric Flin; Olivier Teytaud; Laure Tougne (Theoretical Foundations of Computer Vision, 2002)

Contrôle du risque multiple pour la sélection de règles d'association significatives. - Stéphane Lallich; Elie Prudhomme; Olivier Teytaud (EGC, 2004)

Algorithms (X, sigma, eta): Quasi-random Mutations for Evolution Strategies. - Anne Auger; Mohamed Jebalia; Olivier Teytaud (Artificial Evolution, 2005)

Systèmes inductifs-déductifs: une approche statistique. - Nicolas Baskiotis; Michèle Sebag; Olivier Teytaud (CAP, 2005)

Taylor-based pseudo-metrics for random process fitting in dynamic programming: expected loss minimization and risk management. - Sylvain Gelly; Jérémie Mary; Olivier Teytaud (CAP, 2005)

Statistical asymptotic and non-asymptotic consistency of bayesian networks: convergence to the right structure and consistent probability estimates. - Sylvain Gelly; Olivier Teytaud (CAP, 2005)

Apprentissage statistique et programmation génétique: la croissance du code est-elle inévitable? - Sylvain Gelly; Olivier Teytaud; Nicolas Bredèche; Marc Schoenauer (CAP, 2005)

Multi-objective Multi-modal Optimization for Mining Spatio-temporal Patterns. - Nicolas Tarrisson; Michèle Sebag; Olivier Teytaud; Julien Lefèvre; Sylvain Baillet (CAP, 2005)

Local and global order 3/2 convergence of a surrogate evolutionary algorithm. - Anne Auger; Marc Schoenauer; Olivier Teytaud (GECCO, 2005)

A statistical learning theory approach of bloat. - Sylvain Gelly; Olivier Teytaud; Nicolas Bredèche; Marc Schoenauer (GECCO, 2005)

A Multi-Objective Multi-Modal Optimization Approach for Mining Stable Spatio-Temporal Patterns. - Michèle Sebag; Nicolas Tarrisson; Olivier Teytaud; Julien Lefèvre; Sylvain Baillet (IJCAI, 2005)

Adaptive estimation of normals and surface area for discrete 3-D objects: application to snow binary data from X-ray tomography. - Frédéric Flin; Jean-Bruno Brzoska; David Coeurjolly; Romeu André Pieritz; Bernard Lesaffre; Cécile Coléou; Pascal Lamboley; Olivier Teytaud; Gérard Vignoles; Jean-François Delesse (IEEE Trans. Image Process., 2005)

Resource-Aware Parameterizations of EDA. - Sylvain Gelly; Olivier Teytaud; Christian Gagné 001 (IEEE Congress on Evolutionary Computation, 2006)

Why Simulation-Based Approachs with Combined Fitness are a Good Approach for Mining Spaces of Turing-equivalent Functions. - Olivier Teytaud (IEEE Congress on Evolutionary Computation, 2006)

Learning for stochastic dynamic programming. - Sylvain Gelly; Jérémie Mary; Olivier Teytaud (ESANN, 2006)

General Lower Bounds for Evolutionary Algorithms. - Olivier Teytaud; Sylvain Gelly (PPSN, 2006)

On the Ultimate Convergence Rates for Isotropic Algorithms and the Best Choices Among Various Forms of Isotropy. - Olivier Teytaud; Sylvain Gelly; Jérémie Mary (PPSN, 2006)

Optimal estimation for Large-Eddy Simulation of turbulence and application to the analysis of subgrid models - Antoine Moreau; Olivier Teytaud; Jean-Pierre Bertoglio (CoRR, 2006)

Bayesian Networks: a Non-Frequentist Approach for Parametrization, and a more Accurate Structural Complexity Measure Bayesian Networks Learning. - Sylvain Gelly; Olivier Teytaud (Rev. d'Intelligence Artif., 2006)

Universal Consistency and Bloat in GP Some theoretical considerations about Genetic Programming from a Statistical Learning Theory viewpoint. - Sylvain Gelly; Olivier Teytaud; Nicolas Bredèche; Marc Schoenauer (Rev. d'Intelligence Artif., 2006)

Conditioning, Halting Criteria and Choosing lambda. - Olivier Teytaud (Artificial Evolution, 2007)

On the adaptation of noise level for stochastic optimization. - Olivier Teytaud; Anne Auger (IEEE Congress on Evolutionary Computation, 2007)

Continuous lunches are free! - Anne Auger; Olivier Teytaud (GECCO, 2007)

DCMA: yet another derandomization in covariance-matrix-adaptation. - Olivier Teytaud; Sylvain Gelly (GECCO, 2007)

Nonlinear programming in approximate dynamic programming - bang-bang solutions, stock-management and unsmooth penalties. - Olivier Teytaud; Sylvain Gelly (ICINCO-ICSO, 2007)

Active learning in regression, with application to stochastic dynamic programming. - Olivier Teytaud; Sylvain Gelly; Jérémie Mary (ICINCO-ICSO, 2007)

Slightly Beyond Turing's Computability for Studying Genetic Programming. - Olivier Teytaud (MCU, 2007)

Comparison-Based Algorithms Are Robust and Randomized Algorithms Are Anytime. - Sylvain Gelly; Sylvie Ruette; Olivier Teytaud (Evol. Comput., 2007)

On the Hardness of Offline Multi-objective Optimization. - Olivier Teytaud (Evol. Comput., 2007)

Association Rule Interestingness: Measure and Statistical Validation. - Stéphane Lallich; Olivier Teytaud; Elie Prudhomme (Quality Measures in Data Mining, 2007)

The Parallelization of Monte-Carlo Planning - Parallelization of MC-Planning. - Sylvain Gelly; Jean-Baptiste Hoock; Arpad Rimmel; Olivier Teytaud; Y. Kalemkarian (ICINCO-ICSO, 2008)

When Does Quasi-random Work?. - Olivier Teytaud (PPSN, 2008)

Lower Bounds for Evolution Strategies Using VC-Dimension. - Olivier Teytaud; Hervé Fournier (PPSN, 2008)

Adding Expert Knowledge and Exploration in Monte-Carlo Tree Search. - Guillaume Chaslot; Christophe Fiter; Jean-Baptiste Hoock; Arpad Rimmel; Olivier Teytaud (ACG, 2009)

Creating an Upper-Confidence-Tree Program for Havannah. - Fabien Teytaud; Olivier Teytaud (ACG, 2009)

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

A Statistical Learning Perspective of Genetic Programming. - Nur Merve Amil; Nicolas Bredèche; Christian Gagné 001; Sylvain Gelly; Marc Schoenauer; Olivier Teytaud (EuroGP, 2009)

Grid Coevolution for Adaptive Simulations: Application to the Building of Opening Books in the Game of Go. - Pierre Audouard; Guillaume Chaslot; Jean-Baptiste Hoock; Julien Perez; Arpad Rimmel; Olivier Teytaud (EvoWorkshops, 2009)

On the Parallel Speed-Up of Estimation of Multivariate Normal Algorithm and Evolution Strategies. - Fabien Teytaud; Olivier Teytaud (EvoWorkshops, 2009)

A novel ontology for computer go knowledge management. - Chang-Shing Lee; Mei-Hui Wang; Tzung-Pei Hong; Guillaume Chaslot; Jean-Baptiste Hoock; Arpad Rimmel; Olivier Teytaud; Yau-Hwang Kuo (FUZZ-IEEE, 2009)

Optimizing low-discrepancy sequences with an evolutionary algorithm. - François-Michel De Rainville; Christian Gagné 001; Olivier Teytaud; Denis Laurendeau (GECCO, 2009)

Optimal robust expensive optimization is tractable. - Philippe Rolet; Michèle Sebag; Olivier Teytaud (GECCO, 2009)

Why one must use reweighting in estimation of distribution algorithms. - Fabien Teytaud; Olivier Teytaud (GECCO, 2009)

Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm. - Philippe Rolet; Michèle Sebag; Olivier Teytaud (ECML/PKDD (2), 2009)

Combiner connaissances expertes, hors-ligne, transientes et en ligne pour l'exploration Monte-Carlo. Apprentissage et MC. - Guillaume Chaslot; L. Chatriot; Christophe Fiter; Sylvain Gelly; Jean-Baptiste Hoock; Julien Perez; Arpad Rimmel; Olivier Teytaud (Rev. d'Intelligence Artif., 2009)

The Computational Intelligence of MoGo Revealed in Taiwan's Computer Go Tournaments. - Chang-Shing Lee; Mei-Hui Wang; Guillaume Chaslot; Jean-Baptiste Hoock; Arpad Rimmel; Olivier Teytaud; Shang-Rong Tsai; Shun-Chin Hsu; Tzung-Pei Hong (IEEE Trans. Comput. Intell. AI Games, 2009)

Scalability and Parallelization of Monte-Carlo Tree Search. - Amine Bourki; Guillaume Chaslot; Matthieu Coulm; Vincent Danjean; Hassen Doghmen; Jean-Baptiste Hoock; Thomas Hérault; Arpad Rimmel; Fabien Teytaud; Olivier Teytaud; Paul Vayssière; Ziqin Yut (Computers and Games, 2010)

A Principled Method for Exploiting Opening Books. - Romaric Gaudel; Jean-Baptiste Hoock; Julien Perez; Nataliya Sokolovska; Olivier Teytaud (Computers and Games, 2010)

Biasing Monte-Carlo Simulations through RAVE Values. - Arpad Rimmel; Fabien Teytaud; Olivier Teytaud (Computers and Games, 2010)

On the huge benefit of decisive moves in Monte-Carlo Tree Search algorithms. - Fabien Teytaud; Olivier Teytaud (CIG, 2010)

Bandit-Based Genetic Programming. - Jean-Baptiste Hoock; Olivier Teytaud (EuroGP, 2010)

Adaptive Noisy Optimization. - Philippe Rolet; Olivier Teytaud (EvoApplications (1), 2010)

Parameter Tuning by Simple Regret Algorithms and Multiple Simultaneous Hypothesis Testing. - Amine Bourki; Matthieu Coulm; Philippe Rolet; Olivier Teytaud; Paul Vayssière (ICINCO (1), 2010)

Consistency Modifications for Automatically Tuned Monte-Carlo Tree Search. - Vincent Berthier; Hassen Doghmen; Olivier Teytaud (LION, 2010)

Bandit-Based Estimation of Distribution Algorithms for Noisy Optimization: Rigorous Runtime Analysis. - Philippe Rolet; Olivier Teytaud (LION, 2010)

Complexity Bounds for Batch Active Learning in Classification. - Philippe Rolet; Olivier Teytaud (ECML/PKDD (3), 2010)

Log(lambda) Modifications for Optimal Parallelism. - Fabien Teytaud; Olivier Teytaud (PPSN (1), 2010)

Continuous Lunches Are Free Plus the Design of Optimal Optimization Algorithms. - Anne Auger; Olivier Teytaud (Algorithmica, 2010)

Intelligent Agents for the Game of Go. - Jean-Baptiste Hoock; Chang-Shing Lee; Arpad Rimmel; Fabien Teytaud; Mei-Hui Wang; Olivier Teytaud (IEEE Comput. Intell. Mag., 2010)

The Game of Go @ IEEE WCCI 2010 [Society Briefs]. - Chang-Shing Lee; Mei-Hui Wang; Olivier Teytaud; Yuan-Liang Wang (IEEE Comput. Intell. Mag., 2010)

Special Issue on Monte Carlo Techniques and Computer Go. - Chang-Shing Lee; Martin Müller 003; Olivier Teytaud (IEEE Trans. Comput. Intell. AI Games, 2010)

Current Frontiers in Computer Go. - Arpad Rimmel; Olivier Teytaud; Chang-Shing Lee; Shi-Jim Yen; Mei-Hui Wang; Shang-Rong Tsai (IEEE Trans. Comput. Intell. AI Games, 2010)

Lower Bounds for Evolution Strategies. - Olivier Teytaud (Theory of Randomized Search Heuristics, 2011)

Towards a Solution of 7x7 Go with Meta-MCTS. - Cheng-Wei Chou; Ping-Chiang Chou; Hassen Doghmen; Chang-Shing Lee; Tsan-Cheng Su; Fabien Teytaud; Olivier Teytaud; Hui-Min Wang; Mei-Hui Wang; Li-Wen Wu; Shi-Jim Yen (ACG, 2011)

Online Sparse Bandit for Card Games. - David Lupien St-Pierre; Quentin Louveaux; Olivier Teytaud (ACG, 2011)

A Rigorous Runtime Analysis for Quasi-Random Restarts and Decreasing Stepsize. - Marc Schoenauer; Fabien Teytaud; Olivier Teytaud (Artificial Evolution, 2011)

Computational and human intelligence in blind Go. - Ping-Chiang Chou; Hassen Doghmen; Chang-Shing Lee; Fabien Teytaud; Olivier Teytaud; Hui-Min Wang; Mei-Hui Wang; Li-Wen Wu; Shi-Jim Yen (CIG, 2011)

Random positions in Go. - Bernard Helmstetter; Chang-Shing Lee; Fabien Teytaud; Olivier Teytaud; Mei-Hui Wang; Shi-Jim Yen (CIG, 2011)

Lemmas on partial observation, with application to phantom games. - Fabien Teytaud; Olivier Teytaud (CIG, 2011)

Revisiting Monte-Carlo Tree Search on a Normal Form Game: NoGo. - Cheng-Wei Chou; Olivier Teytaud; Shi-Jim Yen (EvoApplications (1), 2011)

Upper Confidence Trees with Short Term Partial Information. - Olivier Teytaud; Sébastien Flory (EvoApplications (1), 2011)

Handling expensive optimization with large noise. - Rémi Coulom; Philippe Rolet; Nataliya Sokolovska; Olivier Teytaud (FOGA, 2011)

Simple tools for multimodal optimization. - Marc Schoenauer; Fabien Teytaud; Olivier Teytaud (GECCO (Companion), 2011)

Comparison-based complexity of multiobjective optimization. - Olivier Teytaud (GECCO, 2011)

Q-Learning with Double Progressive Widening: Application to Robotics. - Nataliya Sokolovska; Olivier Teytaud; Mario Milone (ICONIP (3), 2011)

Intelligent agents for games and computer Go. - Chang-Shing Lee; Olivier Teytaud (IEEE IA, 2011)

Continuous Upper Confidence Trees. - Adrien Couëtoux; Jean-Baptiste Hoock; Nataliya Sokolovska; Olivier Teytaud; Nicolas Bonnard (LION, 2011)

Lower Bounds for Comparison Based Evolution Strategies Using VC-dimension and Sign Patterns. - Hervé Fournier; Olivier Teytaud (Algorithmica, 2011)

Human vs. Computer Go Competition in FUZZ-IEEE 2011. - Shi-Jim Yen; Shih-Yuan Chiu; Cheng-Wei Chou; Chang-Shing Lee; Hassen Doghmen; Fabien Teytaud; Olivier Teytaud (J. Int. Comput. Games Assoc., 2011)

The IEEE SSCI 2011 Human vs. Computer Go Competition. - Shi-Jim Yen; Cheng-Wei Chou; Chang-Shing Lee; Hassen Doghmen; Olivier Teytaud (J. Int. Comput. Games Assoc., 2011)

Continuous RAVE. - Adrien Couëtoux; Mario Milone; Mátyás Brendel; Hassen Doghmen; Michèle Sebag; Olivier Teytaud (ACML, 2011)

Improving the Exploration in Upper Confidence Trees. - Adrien Couëtoux; Hassen Doghmen; Olivier Teytaud (LION, 2012)

Upper Confidence Tree-Based Consistent Reactive Planning Application to MineSweeper. - Michèle Sebag; Olivier Teytaud (LION, 2012)

Strategic Choices: Small Budgets and Simple Regret. - Cheng-Wei Chou; Ping-Chiang Chou; Chang-Shing Lee; David Lupien Saint-Pierre; Olivier Teytaud; Mei-Hui Wang; Li-Wen Wu; Shi-Jim Yen (TAAI, 2012)

The grand challenge of computer Go: Monte Carlo tree search and extensions. - Sylvain Gelly; Levente Kocsis; Marc Schoenauer; Michèle Sebag; David Silver; Csaba Szepesvári; Olivier Teytaud (Commun. ACM, 2012)

Computational Intelligence Meets Game of Go @ IEEE WCCI 2012 [Society Briefs]. - Chang-Shing Lee; Olivier Teytaud; Mei-Hui Wang; Shi-Jim Yen (IEEE Comput. Intell. Mag., 2012)

Human vs. Machine Go Competition in IEEE WCCCI 2012. - Chang-Shing Lee; Mei-Hui Wang; Olivier Teytaud; Shi-Jim Yen (J. Int. Comput. Games Assoc., 2012)

The Frontier of Decidability in Partially Observable Recursive Games. - David Auger; Olivier Teytaud (Int. J. Found. Comput. Sci., 2012)

Genetic fuzzy markup language for game of NoGo. - Chang-Shing Lee; Mei-Hui Wang; Yu-Jen Chen; Hani Hagras; Meng-Jhen Wu; Olivier Teytaud (Knowl. Based Syst., 2012)

Evolutionary optimization of low-discrepancy sequences. - François-Michel De Rainville; Christian Gagné 001; Olivier Teytaud; Denis Laurendeau (ACM Trans. Model. Comput. Simul., 2012)

Exploration vs Exploitation vs Safety: Risk-Aware Multi-Armed Bandits. - Nicolas Galichet; Michèle Sebag; Olivier Teytaud (ACML, 2013)

Linear Convergence of Evolution Strategies with Derandomized Sampling Beyond Quasi-Convex Functions. - Jérémie Decock; Olivier Teytaud (Artificial Evolution, 2013)

Log-log Convergence for Noisy Optimization. - Sandra Astete Morales; Jialin Liu 001; Olivier Teytaud (Artificial Evolution, 2013)

Fuzzy Ontologies for the Game of Go. - Chang-Shing Lee; Mei-Hui Wang; Olivier Teytaud (On Fuzziness (1), 2013)

Noisy optimization complexity under locality assumption. - Jérémie Decock; Olivier Teytaud (FOGA, 2013)

T2FML-based adaptive assessment system for computer game of Go. - Chang-Shing Lee; Meng-Jhen Wu; Mei-Hui Wang; Olivier Teytaud; Hui-Min Wang; Shi-Jim Yen (FUZZ-IEEE, 2013)

Noisy optimization convergence rates. - Sandra Astete Morales; Jialin Liu 001; Olivier Teytaud (GECCO (Companion), 2013)

Continuous Upper Confidence Trees with Polynomial Exploration - Consistency. - David Auger; Adrien Couëtoux; Olivier Teytaud (ECML/PKDD (1), 2013)

Sparse binary zero-sum games. - David Auger; Jialin Liu 001; Sylvie Ruette; David Lupien St-Pierre; Olivier Teytaud (ACML, 2014)

The Nash and the bandit approaches for adversarial portfolios. - David Lupien St-Pierre; Olivier Teytaud (CIG, 2014)

Direct Model-Predictive Control. - Jean-Joseph Christophe; Jérémie Decock; Olivier Teytaud (ESANN, 2014)

Meta Online Learning: Experiments on a Unit Commitment Problem. - Jialin Liu 001; Olivier Teytaud (ESANN, 2014)

Sharing Information in Adversarial Bandit. - David Lupien St-Pierre; Olivier Teytaud (EvoApplications, 2014)

A mathematically derived number of resamplings for noisy optimization. - Jialin Liu 001; David Lupien St-Pierre; Olivier Teytaud (GECCO (Companion), 2014)

Algorithm Portfolios for Noisy Optimization: Compare Solvers Early. - Marie-Liesse Cauwet; Jialin Liu 001; Olivier Teytaud (LION, 2014)

Exploration vs Exploitation vs Safety: Risk-averse Multi-Armed Bandits. - Nicolas Galichet; Michèle Sebag; Olivier Teytaud (CoRR, 2014)

Strategic Choices in Optimization. - Cheng-Wei Chou; Ping-Chiang Chou; Jean-Joseph Christophe; Adrien Couëtoux; Pierre de Freminville; Nicolas Galichet; Chang-Shing Lee; Jialin Liu 001; David Lupien Saint-Pierre; Michèle Sebag; Olivier Teytaud; Mei-Hui Wang; et al. (J. Inf. Sci. Eng., 2014)

Convergence Rates of Evolutionary Algorithms and Parallel Evolutionary Algorithms. - Fabien Teytaud; Olivier Teytaud (Theory and Principled Methods for the Design of Metaheuristics, 2014)

Designing an Optimal Search Algorithm with Respect to Prior Information. - Olivier Teytaud; Emmanuel Vázquez (Theory and Principled Methods for the Design of Metaheuristics, 2014)

Go Complexities. - Abdallah Saffidine; Olivier Teytaud; Shi-Jim Yen (ACG, 2015)

On the Codimension of the Set of Optima: Large Scale Optimisation with Few Relevant Variables. - Vincent Berthier; Olivier Teytaud (Artificial Evolution, 2015)

Variance Reduction in Population-Based Optimization: Application to Unit Commitment. - Jean-Joseph Christophe; Jérémie Decock; Jialin Liu 001; Olivier Teytaud (Artificial Evolution, 2015)

Quasi-random Numbers Improve the CMA-ES on the BBOB Testbed. - Olivier Teytaud (Artificial Evolution, 2015)

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 001; Tsan-Cheng Su; Fabien Teytaud; Olivier Teytaud; Shi-Jim Yen (CEC, 2015)

Nash reweighting of Monte Carlo simulations: Tsumego. - David Lupien St-Pierre; Jialin Liu 001; Olivier Teytaud (CEC, 2015)

Depth, balancing, and limits of the Elo model. - Marie-Liesse Cauwet; Olivier Teytaud; Tristan Cazenave; Abdallah Saffidine; Hua-Min Liang; Shi-Jim Yen; Hung-Hsuan Lin; I-Chen Wu (CIG, 2015)

The rectangular seeds of Domineering. - Tristan Cazenave; Jialin Liu 001; Olivier Teytaud (CIG, 2015)

Parallel Evolutionary Algorithms Performing Pairwise Comparisons. - Marie-Liesse Cauwet; Olivier Teytaud; Shih-Yuan Chiu; Kuo-Min Lin; Shi-Jim Yen; David Lupien St-Pierre; Fabien Teytaud (FOGA, 2015)

Evolution Strategies with Additive Noise: A Convergence Rate Lower Bound. - Sandra Astete Morales; Marie-Liesse Cauwet; Olivier Teytaud (FOGA, 2015)

Item response theory with fuzzy markup language for parameter estimation and validation. - Mei-Hui Wang; Chi-Shiang Wang; Chang-Shing Lee; Olivier Teytaud; Jialin Liu 001; Su-Wei Lin; Pi-Hsia Hung (FUZZ-IEEE, 2015)

Variance Reduction in Population-Based Optimization: Application to Unit Commitment. - Jérémie Decock; Jialin Liu 001; Olivier Teytaud (GECCO (Companion), 2015)

Criteria and Convergence Rates in Noisy Optimization. - Sandra Astete Morales; Marie-Liesse Cauwet; Olivier Teytaud (GECCO (Companion), 2015)

Analysis of runtime of optimization algorithms for noisy functions over discrete codomains. - Youhei Akimoto; Sandra Astete Morales; Olivier Teytaud (Theor. Comput. Sci., 2015)

T2FS-Based Adaptive Linguistic Assessment System for Semantic Analysis and Human Performance Evaluation on Game of Go. - Chang-Shing Lee; Mei-Hui Wang; Meng-Jhen Wu; Olivier Teytaud; Shi-Jim Yen (IEEE Trans. Fuzzy Syst., 2015)

Fast Seed-Learning Algorithms for Games. - Jialin Liu 001; Olivier Teytaud; Tristan Cazenave (Computers and Games, 2016)

Learning opening books in partially observable games: Using random seeds in Phantom Go. - Tristan Cazenave; Jialin Liu 001; Fabien Teytaud; Olivier Teytaud (CIG, 2016)

Noisy Optimization: Fast Convergence Rates with Comparison-Based Algorithms. - Marie-Liesse Cauwet; Olivier Teytaud (GECCO, 2016)

Analysis of Different Types of Regret in Continuous Noisy Optimization. - Sandra Astete Morales; Marie-Liesse Cauwet; Olivier Teytaud (GECCO, 2016)

QR Mutations Improve Many Evolution Strategies: A Lot On Highly Multimodal Problems. - Fabien Teytaud; Olivier Teytaud (GECCO (Companion), 2016)

Multivariate bias reduction in capacity expansion planning. - Marie-Liesse Cauwet; Olivier Teytaud (PSCC, 2016)

Algorithm portfolios for noisy optimization. - Marie-Liesse Cauwet; Jialin Liu 001; Baptiste Rozière; Olivier Teytaud (Ann. Math. Artif. Intell., 2016)

Scenario-based decision-making for power systems investment planning. - Jialin Liu 001; Olivier Teytaud (CoRR, 2016)

Automatically Reinforcing a Game AI. - David Lupien St-Pierre; Jean-Baptiste Hoock; Jialin Liu 001; Fabien Teytaud; Olivier Teytaud (CoRR, 2016)

Simple and cumulative regret for continuous noisy optimization. - Sandra Astete Morales; Marie-Liesse Cauwet; Jialin Liu 001; Olivier Teytaud (Theor. Comput. Sci., 2016)

Boosting a Bridge Artificial Intelligence. - Véronique Ventos; Yves Costel; Olivier Teytaud; Solène Thépaut Ventos (ICTAI, 2017)

Toward Optimal Run Racing: Application to Deep Learning Calibration. - Olivier Bousquet; Sylvain Gelly; Karol Kurach; Marc Schoenauer; Michèle Sebag; Olivier Teytaud; Damien Vincent (CoRR, 2017)

Critical Hyper-Parameters: No Random, No Cry. - Olivier Bousquet; Sylvain Gelly; Karol Kurach; Olivier Teytaud; Damien Vincent (CoRR, 2017)

Better Text Understanding Through Image-To-Text Transfer. - Karol Kurach; Sylvain Gelly; Michal Jastrzebski; Philip Häusser; Olivier Teytaud; Damien Vincent; Olivier Bousquet (CoRR, 2017)

Le bridge, nouveau défi de l'intelligence artificielle ? - Véronique Ventos; Olivier Teytaud (Rev. d'Intelligence Artif., 2017)

Surprising Strategies Obtained by Stochastic Optimization in Partially Observable Games. - Marie-Liesse Cauwet; Olivier Teytaud (CEC, 2018)

Exact Distributed Training: Random Forest with Billions of Examples. - Mathieu Guillame-Bert; Olivier Teytaud (CoRR, 2018)

PSO-Based Fuzzy Markup Language for Student Learning Performance Evaluation and Educational Application. - Chang-Shing Lee; Mei-Hui Wang; Chi-Shiang Wang; Olivier Teytaud; Jialin Liu 001; Su-Wei Lin; Pi-Hsia Hung (IEEE Trans. Fuzzy Syst., 2018)

Consistent population control: generate plenty of points, but with a bit of resampling. - Vasil Khalidov; Maxime Oquab; Jérémy Rapin; Olivier Teytaud (FOGA, 2019)

Openly revisiting derivative-free optimization. - Jérémy Rapin; Pauline Dorval; Jules Pondard; Nicolas Vasilache; Marie-Liesse Cauwet; Camille Couprie; Olivier Teytaud (GECCO (Companion), 2019)

Exploring the MLDA benchmark on the nevergrad platform. - Jérémy Rapin; Marcus Gallagher; Pascal Kerschke; Mike Preuss; Olivier Teytaud (GECCO (Companion), 2019)

A Simple Yet Effective Resampling Rule in Noisy Evolutionary Optimization. - Jialin Liu 001; Olivier Teytaud (SSCI, 2019)

Efficient Decision Making under Uncertainty in a Power System Investment Problem. - Jialin Liu 001; Olivier Teytaud (SSCI, 2019)

Inspirational Adversarial Image Generation. - Morgane Rivière; Olivier Teytaud; Jérémy Rapin; Yann LeCun; Camille Couprie (CoRR, 2019)

Yet another but more efficient black-box adversarial attack: tiling and evolution strategies. - Laurent Meunier; Jamal Atif; Olivier Teytaud (CoRR, 2019)

Fully Parallel Hyperparameter Search: Reshaped Space-Filling. - Marie-Liesse Cauwet; Camille Couprie; Julien Dehos; Pauline Luc; Jérémy Rapin; Morgane Rivière; Fabien Teytaud; Olivier Teytaud (CoRR, 2019)

Artificial Intelligence for Games. - Bruno Bouzy; Tristan Cazenave; Vincent Corruble; Olivier Teytaud (A Guided Tour of Artificial Intelligence Research (2) (II), 2020)

EvolGAN: Evolutionary Generative Adversarial Networks. - Baptiste Rozière; Fabien Teytaud; Vlad Hosu; Hanhe Lin; Jérémy Rapin; Mariia Zameshina; Olivier Teytaud (ACCV (4), 2020)

Versatile black-box optimization. - Jialin Liu 001; Antoine Moreau; Mike Preuss; Jérémy Rapin; Baptiste Rozière; Fabien Teytaud; Olivier Teytaud (GECCO, 2020)

Population control meets doob's martingale theorems: the noise-free multimodal case. - Marie-Liesse Cauwet; Olivier Teytaud (GECCO Companion, 2020)

Open source evolutionary structured optimization. - Jérémy Rapin; Pauline Bennet; Emmanuel Centeno; Daniel Haziza; Antoine Moreau; Olivier Teytaud (GECCO Companion, 2020)

Evolutionary super-resolution. - Baptiste Rozière; Nathanaël Carraz Rakotonirina; Vlad Hosu; Hanhe Lin; Andry Rasoanaivo; Olivier Teytaud; Camille Couprie (GECCO Companion, 2020)

Fully Parallel Hyperparameter Search: Reshaped Space-Filling. - Marie-Liesse Cauwet; Camille Couprie; Julien Dehos; Pauline Luc; Jérémy Rapin; Morgane Rivière; Fabien Teytaud; Olivier Teytaud; Nicolas Usunier (ICML, 2020)

Tarsier: Evolving Noise Injection in Super-Resolution GANs. - Baptiste Rozière; Nathanaël Carraz Rakotonirina; Vlad Hosu; Andry Rasoanaivo; Hanhe Lin; Camille Couprie; Olivier Teytaud (ICPR, 2020)

Adversarial Attacks on Linear Contextual Bandits. - Evrard Garcelon; Baptiste Rozière; Laurent Meunier; Jean Tarbouriech; Olivier Teytaud; Alessandro Lazaric; Matteo Pirotta (NeurIPS, 2020)

On Averaging the Best Samples in Evolutionary Computation. - Laurent Meunier; Yann Chevaleyre; Jérémy Rapin; Clément W. Royer; Olivier Teytaud (PPSN (2), 2020)

Variance Reduction for Better Sampling in Continuous Domains. - Laurent Meunier; Carola Doerr; Jérémy Rapin; Olivier Teytaud (PPSN (1), 2020)

Proving μ>1. - Laurent Meunier; Yann Chevaleyre; Jérémy Rapin; Clément W. Royer; Olivier Teytaud (CoRR, 2020)

Polygames: Improved zero learning. - Tristan Cazenave; Yen-Chi Chen; Guan-Wei Chen; Shi-Yu Chen; Xian-Dong Chiu; Julien Dehos; Maria Elsa; Qucheng Gong; Hengyuan Hu; Vasil Khalidov; Cheng-Ling Li; Hsin-I Lin; et al. (J. Int. Comput. Games Assoc., 2020)

Asymptotic convergence rates for averaging strategies. - Laurent Meunier; Iskander Legheraba; Yann Chevaleyre; Olivier Teytaud (FOGA, 2021)

Transfer of Fully Convolutional Policy-Value Networks Between Games and Game Variants. - Dennis J. N. J. Soemers; Vegard Mella; Éric Piette; Matthew Stephenson; Cameron Browne; Olivier Teytaud (CoRR, 2021)

Deep learning for general game playing with Ludii and Polygames. - Dennis J. N. J. Soemers; Vegard Mella; Cameron Browne; Olivier Teytaud (J. Int. Comput. Games Assoc., 2021)

Seed Optimization Framework on Draughts. - Ching-Nung Lin; Fabien Letouzey; Olivier Teytaud; Shi-Jim Yen (J. Inf. Sci. Eng., 2021)

Inspirational Adversarial Image Generation. - Baptiste Rozière; Morgane Rivière; Olivier Teytaud; Jérémy Rapin; Yann LeCun; Camille Couprie (IEEE Trans. Image Process., 2021)

CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research. - Chris Cummins; Bram Wasti; Jiadong Guo; Brandon Cui; Jason Ansel; Sahir Gomez; Somya Jain; Jia Liu; Olivier Teytaud; Benoit Steiner; Yuandong Tian; Hugh Leather (CGO, 2022)

Multi-objective Genetic Programming for Explainable Reinforcement Learning. - Mathurin Videau; Alessandro Ferreira Leite; Olivier Teytaud; Marc Schoenauer (EuroGP, 2022)

Fairness in generative modeling: do it unsupervised! - Mariia Zameshina; Olivier Teytaud; Fabien Teytaud; Vlad Hosu; Nathanaël Carraz Rakotonirina; Laurent Najman; Markus Wagner 007 (GECCO Companion, 2022)

Improving Nevergrad's Algorithm Selection Wizard NGOpt Through Automated Algorithm Configuration. - Risto Trajanov; Ana Nikolikj; Gjorgjina Cenikj; Fabien Teytaud; Mathurin Videau; Olivier Teytaud; Tome Eftimov; Manuel López-Ibáñez 001; Carola Doerr (PPSN (1), 2022)

Fairness in generative modeling. - Mariia Zameshina; Olivier Teytaud; Fabien Teytaud; Vlad Hosu; Nathanaël Carraz; Laurent Najman; Markus Wagner 007 (CoRR, 2022)

Black-Box Optimization Revisited: Improving Algorithm Selection Wizards Through Massive Benchmarking. - Laurent Meunier; Herilalaina Rakotoarison; Pak-Kan Wong; Baptiste Rozière; Jérémy Rapin; Olivier Teytaud; Antoine Moreau; Carola Doerr (IEEE Trans. Evol. Comput., 2022)

Interactive Latent Diffusion Model. - Mathurin Videau; Nickolai Knizev; Alessandro Ferreira Leite; Marc Schoenauer; Olivier Teytaud (GECCO, 2023)

Diverse Diffusion: Enhancing Image Diversity in Text-to-Image Generation. - Mariia Zameshina; Olivier Teytaud; Laurent Najman (CoRR, 2023)

PrivacyGAN: robust generative image privacy. - Mariia Zameshina; Marlène Careil; Olivier Teytaud; Laurent Najman (CoRR, 2023)

Towards a General Transfer Approach for Policy-Value Networks. - Dennis J. N. J. Soemers; Vegard Mella; Éric Piette; Matthew Stephenson; Cameron Browne; Olivier Teytaud (Trans. Mach. Learn. Res., 2023)

Ellawin/tuto_global_optimization_photonics: v1. - Pauline Bennet; Olivier Teytaud; Peter R. Wiecha; Denis Langevin; Antoine Moreau; Abdourahman Khaireh-Walieh (Zenodo, 2023)

Log-normal Mutations and their Use in Detecting Surreptitious Fake Images. - Ismail Labiad; Thomas Bäck; Pierre Fernandez; Laurent Najman; Tom Sander; Furong Ye; Mariia Zameshina; Olivier Teytaud (CoRR, 2024)

Evolutionary Retrofitting. - Mathurin Videau; Mariia Zameshina; Alessandro Ferreira Leite; Laurent Najman; Marc Schoenauer; Olivier Teytaud (CoRR, 2024)

Mixture of Experts in Image Classification: What's the Sweet Spot? - Mathurin Videau; Alessandro Ferreira Leite; Marc Schoenauer; Olivier Teytaud (CoRR, 2024)

Evolutionary Pre-Prompt Optimization for Mathematical Reasoning. - Mathurin Videau; Alessandro Ferreira Leite; Marc Schoenauer; Olivier Teytaud (CoRR, 2024)

Lognormal Mutations and their Use in Detecting Surreptitious Fake Images. - Olivier Teytaud; Mariia Zameshina; Tom Sander; Pierre Fernandez; Furong Ye; Laurent Najman; Thomas Bäck; Ismail Labiad (Trans. Mach. Learn. Res., 2025)

Optimizing With Low Budgets: A Comparison on the Black-Box Optimization Benchmarking Suite and OpenAI Gym. - Elena Raponi; Nathanaël Carraz Rakotonirina; Jérémy Rapin; Carola Doerr; Olivier Teytaud (IEEE Trans. Evol. Comput., 2025)

From Bytes to Ideas: Language Modeling with Autoregressive U-Nets. - Mathurin Videau; Badr Youbi Idrissi; Alessandro Ferreira Leite; Marc Schoenauer; Olivier Teytaud; David Lopez-Paz (CoRR, 2025)

Tuning without Peeking: Provable Privacy and Generalization Bounds for LLM Post-Training. - Ismail Labiad; Mathurin Videau; Matthieu Kowalski; Marc Schoenauer; Alessandro Ferreira Leite; Julia Kempe; Olivier Teytaud (CoRR, 2025)