Michèle Sebag

246 papers A* 28A 25B 16C 8Misc 2Journal 68Unranked 84

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Asymmetrical Latent Representation for Individual Treatment Effect Modeling. CoRR Armand Lacombe, Michèle Sebag
2025	A*	`conf`	DCILP: A Distributed Approach for Large-Scale Causal Structure Learning. AAAI Shuyu Dong, Michèle Sebag, Kento Uemura, Akito Fujii, Shuang Chang, Yusuke Koyanagi, Koji Maruhashi
2025	A*	`conf`	Provably Safeguarding a Classifier from OOD and Adversarial Samples. ICLR Nicolas Atienza, Johanne Cohen, Christophe Labreuche, Michèle Sebag
2025	J	`jnl`	Provably Safeguarding a Classifier from OOD and Adversarial Samples: an Extreme Value Theory Approach. CoRR Nicolas Atienza, Christophe Labreuche, Johanne Cohen, Michèle Sebag
2024	A*	`conf`	Cutting the Black Box: Conceptual Interpretation of a Deep Neural Net with Multi-Modal Embeddings and Multi-Criteria Decision Aid. IJCAI Nicolas Atienza, Roman Bresson, Cyriaque Rousselot, Philippe Caillou, Johanne Cohen, Christophe Labreuche, Michèle Sebag
2024	J	`jnl`	DCDILP: a distributed learning method for large-scale causal structure learning. CoRR Shuyu Dong, Michèle Sebag, Kento Uemura, Akito Fujii, Shuang Chang, Yusuke Koyanagi, Koji Maruhashi
2024	—	`conf`	Frugal Generative Modeling for Tabular Data. ECML/PKDD (8) Alice Lacan, Blaise Hanczar, Michèle Sebag
2024	A*	`conf`	Learning Structural Causal Models through Deep Generative Models: Methods, Guarantees, and Challenges. IJCAI Audrey Poinsot, Alessandro Ferreira Leite, Nicolas Chesneau, Michèle Sebag, Marc Schoenauer
2024	J	`jnl`	Learning Structural Causal Models through Deep Generative Models: Methods, Guarantees, and Challenges. CoRR Audrey Poinsot, Alessandro Ferreira Leite, Nicolas Chesneau, Michèle Sebag, Marc Schoenauer
2024	—	`conf`	Modelling Dynamical Systems: Learning ODEs with No Internal ODE Resolution. RP Johanne Cohen, Emmanuel Goutierre, Hayg Guler, Fatios Kapotos, Sida-Bastien Li, Michèle Sebag, Bowen Zhu
2023	—	`conf`	Fairness in job recommendations: estimating, explaining, and reducing gender gaps. AEQUITAS@ECAI Guillaume Bied, Christophe Gaillac, Morgane Hoffmann, Philippe Caillou, Bruno Crépon, Solal Nathan, Michèle Sebag
2023	J	`jnl`	GAN-based data augmentation for transcriptomics: survey and comparative assessment. Bioinform. Alice Lacan, Michèle Sebag, Blaise Hanczar
2023	—	`conf`	RECTO : REcommandation diminuant la Congestion par Transport Optimal. APIA Guillaume Bied, Elia Perennes, Solal Nathan, Victor Naya, Philippe Caillou, Bruno Crépon, Christophe Gaillac, Michèle Sebag
2023	A*	`conf`	Toward Job Recommendation for All. IJCAI Guillaume Bied, Solal Nathan, Elia Perennes, Morgane Hoffmann, Philippe Caillou, Bruno Crépon, Christophe Gaillac, Michèle Sebag
2022	—	`conf`	From Graphs to DAGs: A Low-Complexity Model and a Scalable Algorithm. ECML/PKDD (5) Shuyu Dong, Michèle Sebag
2022	J	`jnl`	From graphs to DAGs: a low-complexity model and a scalable algorithm. CoRR Shuyu Dong, Michèle Sebag
2022	J	`jnl`	High-Dimensional Causal Discovery: Learning from Inverse Covariance via Independence-based Decomposition. CoRR Shuyu Dong, Kento Uemura, Akito Fujii, Shuang Chang, Yusuke Koyanagi, Koji Maruhashi, Michèle Sebag
2022	A*	`conf`	Learning meta-features for AutoML. ICLR Herilalaina Rakotoarison, Louisot Milijaona, Andry Rasoanaivo, Michèle Sebag, Marc Schoenauer
2022	J	`jnl`	Structural Agnostic Modeling: Adversarial Learning of Causal Graphs. J. Mach. Learn. Res. Diviyan Kalainathan, Olivier Goudet, Isabelle Guyon, David Lopez-Paz, Michèle Sebag
2021	J	`jnl`	Boltzmann Tuning of Generative Models. CoRR Victor Berger, Michèle Sebag
2021	J	`jnl`	Cartolabe: A Web-Based Scalable Visualization of Large Document Collections. IEEE Computer Graphics and Applications Philippe Caillou, Jonas Renault, Jean-Daniel Fekete, Anne-Catherine Letournel, Michèle Sebag
2021	J	`jnl`	Frugal Machine Learning. CoRR Mikhail Evchenko, Joaquin Vanschoren, Holger H. Hoos, Marc Schoenauer, Michèle Sebag
2021	Misc	`conf`	I2SL: Learn How to Swarm Autonomous Quadrotors Using Iterative Imitation Supervised Learning. EPIA Omar Shrit, Michèle Sebag
2021	—	`conf`	Important Topics in Causal Analysis: Summary of the CAWS 2021 Round Table Discussion. CAWS Erich Kummerfeld, Thomas Woolf, Will Glad, Michèle Sebag, Sisi Ma
2021	—	`conf`	Iterative Learning for Model Reactive Control: Application to Autonomous Multi-agent Control. ICARA Omar Shrit, David Filliat, Michèle Sebag
2021	A*	`conf`	On the Identifiability of Hierarchical Decision Models. KR Roman Bresson, Johanne Cohen, Eyke Hüllermeier, Christophe Labreuche, Michèle Sebag
2021	—	`conf`	Towards causal modeling of nutritional outcomes. CAWS Ksenia Gasnikova, Olivier Allais, Michèle Sebag
2020	J	`jnl`	Cartolabe: A Web-Based Scalable Visualization of Large Document Collections. CoRR Philippe Caillou, Jonas Renault, Jean-Daniel Fekete, Anne-Catherine Letournel, Michèle Sebag
2020	J	`jnl`	Distribution-Based Invariant Deep Networks for Learning Meta-Features. CoRR Gwendoline de Bie, Herilalaina Rakotoarison, Gabriel Peyré, Michèle Sebag
2020	A*	`conf`	Dynamic Time Lag Regression: Predicting What & When. ICLR Mandar Chandorkar, Cyril Furtlehner, Bala Poduval, Enrico Camporeale, Michèle Sebag
2020	J	`jnl`	From abstract items to latent spaces to observed data and back: Compositional Variational Auto-Encoder. CoRR Victor Berger, Michèle Sebag
2020	J	`jnl`	Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities. Frontiers Big Data Remy Kusters, Dusan Misevic, Hugues Berry, Antoine Cully, Yann Le Cunff, Loic Dandoy, Natalia Díaz Rodríguez, Marion Ficher, Jonathan Grizou, Alice Othmani, Themis Palpanas, Matthieu Komorowski, Patrick Loiseau, Clément Moulin-Frier, Santino Nanini, Daniele Quercia, Michèle Sebag, Françoise Fogelman-Soulié, Sofiane Taleb, Liubov Tupikina, Vaibhav Sahu, Jill-Jênn Vie, Fatima Wehbi
2020	A*	`conf`	Neural Representation and Learning of Hierarchical 2-additive Choquet Integrals. IJCAI Roman Bresson, Johanne Cohen, Eyke Hüllermeier, Christophe Labreuche, Michèle Sebag
2020	J	`jnl`	Variational Auto-Encoder: not all failures are equal. CoRR Victor Berger, Michèle Sebag
2019	—	`conf`	Agnostic Feature Selection. ECML/PKDD (1) Guillaume Doquet, Michèle Sebag
2019	—	`ch.`	Analysis of the AutoML Challenge Series 2015-2018. Automated Machine Learning Isabelle Guyon, Lisheng Sun-Hosoya, Marc Boullé, Hugo Jair Escalante, Sergio Escalera, Zhengying Liu, Damir Jajetic, Bisakha Ray, Mehreen Saeed, Michèle Sebag, Alexander R. Statnikov, Wei-Wei Tu, Evelyne Viegas
2019	J	`jnl`	Automated Machine Learning with Monte-Carlo Tree Search (Extended Version). CoRR Herilalaina Rakotoarison, Marc Schoenauer, Michèle Sebag
2019	A*	`conf`	Automated Machine Learning with Monte-Carlo Tree Search. IJCAI Herilalaina Rakotoarison, Marc Schoenauer, Michèle Sebag
2019	—	`ch.`	Discriminant Learning Machines. Cause Effect Pairs in Machine Learning Diviyan Kalainathan, Olivier Goudet, Michèle Sebag, Isabelle Guyon
2019	—	`conf`	From Abstract Items to Latent Spaces to Observed Data and Back: Compositional Variational Auto-Encoder. ECML/PKDD (1) Victor Berger, Michèle Sebag
2019	—	`ch.`	Learning Bivariate Functional Causal Models. Cause Effect Pairs in Machine Learning Olivier Goudet, Diviyan Kalainathan, Michèle Sebag, Isabelle Guyon
2019	—	`conf`	Multi-Domain Adversarial Learning. ICLR (Poster) Alice Schoenauer Sebag, Louise Heinrich, Marc Schoenauer, Michèle Sebag, Lani F. Wu, Steven J. Altschuler
2019	J	`jnl`	Multi-Domain Adversarial Learning. CoRR Alice Schoenauer Sebag, Louise Heinrich, Marc Schoenauer, Michèle Sebag, Lani F. Wu, Steven J. Altschuler
2019	J	`jnl`	Towards AutoML in the presence of Drift: first results. CoRR Jorge G. Madrid, Hugo Jair Escalante, Eduardo F. Morales, Wei-Wei Tu, Yang Yu, Lisheng Sun-Hosoya, Isabelle Guyon, Michèle Sebag
2018	—	`conf`	ActivMetal: Algorithm Recommendation with Active Meta Learning. IAL@PKDD/ECML Lisheng Sun-Hosoya, Isabelle Guyon, Michèle Sebag
2017	—	`conf`	ASAP.V2 and ASAP.V3: Sequential optimization of an Algorithm Selector and a Scheduler. OASC François Gonard, Marc Schoenauer, Michèle Sebag
2017	J	`jnl`	Alors: An algorithm recommender system. Artif. Intell. Mustafa Misir, Michèle Sebag
2017	—	`ch.`	Grammatical Inference. Encyclopedia of Machine Learning and Data Mining Lorenza Saitta, Michèle Sebag
2017	B	`conf`	Language Modelling for Collaborative Filtering: Application to Job Applicant Matching. ICTAI Thomas Schmitt, François Gonard, Phillipe Caillou, Michèle Sebag
2017	J	`jnl`	Multi-dimensional signal approximation with sparse structured priors using split Bregman iterations. Signal Process. Yoann Isaac, Quentin Barthélemy, Cédric Gouy-Pailler, Michèle Sebag, Jamal Atif
2017	—	`ch.`	Nonstandard Criteria in Evolutionary Learning. Encyclopedia of Machine Learning and Data Mining Michèle Sebag
2017	—	`ch.`	Phase Transitions in Machine Learning. Encyclopedia of Machine Learning and Data Mining Lorenza Saitta, Michèle Sebag
2017	J	`jnl`	Stochastic Gradient Descent: Going As Fast As Possible But Not Faster. CoRR Alice Schoenauer Sebag, Marc Schoenauer, Michèle Sebag
2017	J	`jnl`	Toward Optimal Run Racing: Application to Deep Learning Calibration. CoRR Olivier Bousquet, Sylvain Gelly, Karol Kurach, Marc Schoenauer, Michèle Sebag, Olivier Teytaud, Damien Vincent
2016	—	`conf`	A brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning without Human Intervention. AutoML@ICML Isabelle Guyon, Imad Chaabane, Hugo Jair Escalante, Sergio Escalera, Damir Jajetic, James Robert Lloyd, Núria Macià, Bisakha Ray, Lukasz Romaszko, Michèle Sebag, Alexander R. Statnikov, Sébastien Treguer, Evelyne Viegas
2016	—	`conf`	Anti Imitation-Based Policy Learning. ECML/PKDD (2) Michèle Sebag, Riad Akrour, Basile Mayeur, Marc Schoenauer
2016	—	`conf`	Matching Jobs and Resumes: a Deep Collaborative Filtering Task. GCAI Thomas Schmitt, Phillipe Caillou, Michèle Sebag
2016	J	`jnl`	Multi-dimensional signal approximation with sparse structured priors using split Bregman iterations. CoRR Yoann Isaac, Quentin Barthélemy, Cédric Gouy-Pailler, Michèle Sebag, Jamal Atif
2015	C	`conf`	Collaborative Algorithm Platforms. DATA Michèle Sebag
2015	—	`conf`	Interactive Metric Learning-Based Visual Data Exploration: Application to the Visualization of a Scientific Social Network. ISIP Masaharu Yoshioka, Masahiko Itoh, Michèle Sebag
2014	A	`conf`	A Recommender System for Process Discovery. BPM Joel Ribeiro, Josep Carmona, Mustafa Misir, Michèle Sebag
2014	J	`jnl`	A tour of machine learning: An AI perspective. AI Commun. Michèle Sebag
2014	—	`conf`	Combination of One-Class Support Vector Machines for Classification with Reject Option. ECML/PKDD (1) Blaise Hanczar, Michèle Sebag
2014	J	`jnl`	Constraints, Optimization and Data (Dagstuhl Seminar 14411). Dagstuhl Reports Luc De Raedt, Siegfried Nijssen, Barry O'Sullivan, Michèle Sebag
2014	A	`conf`	Coupling Evolution and Information Theory for Autonomous Robotic Exploration. PPSN Guohua Zhang, Michèle Sebag
2014	J	`jnl`	Data Stream Clustering With Affinity Propagation. IEEE Trans. Knowl. Data Eng. Xiangliang Zhang, Cyril Furtlehner, Cécile Germain-Renaud, Michèle Sebag
2014	—	`conf`	Experimental Design in Dynamical System Identification: A Bandit-Based Active Learning Approach. ECML/PKDD (2) Artémis Llamosi, Adel Mezine, Florence d'Alché-Buc, Véronique Letort, Michèle Sebag
2014	J	`jnl`	Exploration vs Exploitation vs Safety: Risk-averse Multi-Armed Bandits. CoRR Nicolas Galichet, Michèle Sebag, Olivier Teytaud
2014	—	`ch.`	Learning Sparse Features with an Auto-Associator. Growing Adaptive Machines Sébastien Rebecchi, Hélène Paugam-Moisy, Michèle Sebag
2014	A	`conf`	Maximum Likelihood-Based Online Adaptation of Hyper-Parameters in CMA-ES. PPSN Ilya Loshchilov, Marc Schoenauer, Michèle Sebag, Nikolaus Hansen
2014	J	`jnl`	Maximum Likelihood-based Online Adaptation of Hyper-parameters in CMA-ES. CoRR Ilya Loshchilov, Marc Schoenauer, Michèle Sebag, Nikolaus Hansen
2014	A*	`conf`	Programming by Feedback. ICML Marc Schoenauer, Riad Akrour, Michèle Sebag, Jean-Christophe Souplet
2014	J	`jnl`	Strategic Choices in Optimization. J. Inf. Sci. Eng. Cheng-Wei Chou, Ping-Chiang Chou, Jean-Joseph Christophe, Adrien Couëtoux, Pierre de Freminville, Nicolas Galichet, Chang-Shing Lee, Jialin Liu, David Lupien Saint-Pierre, Michèle Sebag, Olivier Teytaud, Mei-Hui Wang, Li-Wen Wu, Shi-Jim Yen
2013	A	`conf`	Bandit-Based Search for Constraint Programming. CP Manuel Loth, Michèle Sebag, Youssef Hamadi, Marc Schoenauer
2013	—	`conf`	Bi-population CMA-ES agorithms with surrogate models and line searches. GECCO (Companion) Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2013	—	`conf`	Collaborative hyperparameter tuning. ICML (2) Rémi Bardenet, Mátyás Brendel, Balázs Kégl, Michèle Sebag
2013	C	`conf`	Exploration vs Exploitation vs Safety: Risk-Aware Multi-Armed Bandits. ACML Nicolas Galichet, Michèle Sebag, Olivier Teytaud
2013	—	`conf`	Fast Adaptive Object Detection towards a Smart Environment by a Mobile Robot. AmI Shigeru Takano, Ilya Loshchilov, David Meunier, Michèle Sebag, Einoshin Suzuki
2013	—	`conf`	Hybridizing Constraint Programming and Monte-Carlo Tree Search: Application to the Job Shop Problem. LION Manuel Loth, Michèle Sebag, Youssef Hamadi, Marc Schoenauer, Christian Schulte
2013	J	`jnl`	Hypervolume indicator and dominance reward based multi-objective Monte-Carlo Tree Search. Mach. Learn. Weijia Wang, Michèle Sebag
2013	A	`conf`	Intensive surrogate model exploitation in self-adaptive surrogate-assisted cma-es (saacm-es). GECCO Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2013	J	`jnl`	KL-based Control of the Learning Schedule for Surrogate Black-Box Optimization. CoRR Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2013	J	`jnl`	Multi-dimensional sparse structured signal approximation using split Bregman iterations CoRR Yoann Isaac, Quentin Barthélemy, Jamal Atif, Cédric Gouy-Pailler, Michèle Sebag
2013	Misc	`conf`	Multi-dimensional sparse structured signal approximation using split bregman iterations. ICASSP Yoann Isaac, Quentin Barthélemy, Jamal Atif, Cédric Gouy-Pailler, Michèle Sebag
2013	J	`jnl`	Sustainable Cooperative Coevolution with a Multi-Armed Bandit CoRR François-Michel De Rainville, Michèle Sebag, Christian Gagné, Marc Schoenauer, Denis Laurendeau
2013	A	`conf`	Sustainable cooperative coevolution with a multi-armed bandit. GECCO François-Michel De Rainville, Michèle Sebag, Christian Gagné, Marc Schoenauer, Denis Laurendeau
2012	—	`conf`	APRIL: Active Preference Learning-Based Reinforcement Learning. ECML/PKDD (2) Riad Akrour, Marc Schoenauer, Michèle Sebag
2012	J	`jnl`	APRIL: Active Preference-learning based Reinforcement Learning CoRR Riad Akrour, Marc Schoenauer, Michèle Sebag
2012	—	`ch.`	Adaptive Operator Selection and Management in Evolutionary Algorithms. Autonomous Search Jorge Maturana, Álvaro Fialho, Frédéric Saubion, Marc Schoenauer, Frédéric Lardeux, Michèle Sebag
2012	J	`jnl`	Alternative Restart Strategies for CMA-ES CoRR Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2012	—	`conf`	Alternative Restart Strategies for CMA-ES. PPSN (1) Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2012	—	`conf`	BenchNN: On the broad potential application scope of hardware neural network accelerators. IISWC Tianshi Chen, Yunji Chen, Marc Duranton, Qi Guo, Atif Hashmi, Mikko H. Lipasti, Andrew Nere, Shi Qiu, Michèle Sebag, Olivier Temam
2012	J	`jnl`	Black-box optimization benchmarking of IPOP-saACM-ES and BIPOP-saACM-ES on the BBOB-2012 noiseless testbed CoRR Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2012	—	`conf`	Black-box optimization benchmarking of IPOP-saACM-ES and BIPOP-saACM-ES on the BBOB-2012 noiseless testbed. GECCO (Companion) Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2012	J	`jnl`	Black-box optimization benchmarking of IPOP-saACM-ES on the BBOB-2012 noisy testbed CoRR Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2012	—	`conf`	Black-box optimization benchmarking of IPOP-saACM-ES on the BBOB-2012 noisy testbed. GECCO (Companion) Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2012	—	`conf`	Black-box optimization benchmarking of NIPOP-aCMA-ES and NBIPOP-aCMA-ES on the BBOB-2012 noiseless testbed. GECCO (Companion) Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2012	—	`ch.`	Continuous Search in Constraint Programming. Autonomous Search Alejandro Arbelaez, Youssef Hamadi, Michèle Sebag
2012	C	`conf`	Multi-objective Monte-Carlo Tree Search. ACML Weijia Wang, Michèle Sebag
2012	J	`jnl`	Pilot, Rollout and Monte Carlo Tree Search Methods for Job Shop Scheduling CoRR Thomas Philip Runarsson, Marc Schoenauer, Michèle Sebag
2012	—	`conf`	Pilot, Rollout and Monte Carlo Tree Search Methods for Job Shop Scheduling. LION Thomas Philip Runarsson, Marc Schoenauer, Michèle Sebag
2012	J	`jnl`	Self-Adaptive Surrogate-Assisted Covariance Matrix Adaptation Evolution Strategy CoRR Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2012	A	`conf`	Self-adaptive surrogate-assisted covariance matrix adaptation evolution strategy. GECCO Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2012	J	`jnl`	The grand challenge of computer Go: Monte Carlo tree search and extensions. Commun. ACM Sylvain Gelly, Levente Kocsis, Marc Schoenauer, Michèle Sebag, David Silver, Csaba Szepesvári, Olivier Teytaud
2012	—	`conf`	Upper Confidence Tree-Based Consistent Reactive Planning Application to MineSweeper. LION Michèle Sebag, Olivier Teytaud
2011	A	`conf`	Adaptive coordinate descent. GECCO Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2011	—	`conf`	Characterizing Anomalous Behaviors and Revising Robotic Controllers. ICDM Workshops David Meunier, Michèle Sebag, Shin Ando
2011	C	`conf`	Continuous RAVE. ACML Adrien Couëtoux, Mario Milone, Mátyás Brendel, Hassen Doghmen, Michèle Sebag, Olivier Teytaud
2011	—	`conf`	Emergence of temporal and spatial synchronous behaviors in a foraging swarm. ECAL Sylvain Chevallier, Nicolas Bredèche, Hélène Paugam-Moisy, Michèle Sebag
2011	C	`conf`	Not All Parents Are Equal for MO-CMA-ES. EMO Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2011	—	`conf`	On-Board Evolutionary Algorithm and Off-Line Rule Discovery for Column Formation in Swarm Robotics. IAT Asuki Kouno, Jean-Marc Montanier, Shigeru Takano, Nicolas Bredèche, Marc Schoenauer, Michèle Sebag, Einoshin Suzuki
2011	—	`conf`	Preference-Based Policy Learning. ECML/PKDD (1) Riad Akrour, Marc Schoenauer, Michèle Sebag
2011	J	`jnl`	Single trial variability in brain-computer interfaces based on motor imagery: Learning in the presence of labeling noise. Int. J. Imaging Syst. Technol. Cédric Gouy-Pailler, Michèle Sebag, Anthony Larue, Antoine Souloumiac
2011	B	`conf`	The Grid Observatory. CCGRID Cécile Germain-Renaud, Alain Cady, Philippe Gauron, Michel Jouvin, Charles Loomis, Janusz Martyniak, Julien Nauroy, Guillaume Philippon, Michèle Sebag
2011	J	`jnl`	Towards Non-Stationary Grid Models. J. Grid Comput. Tamás Éltetö, Cécile Germain-Renaud, Pascal Bondon, Michèle Sebag
2011	—	`conf`	Using SVM to Avoid Humans: A Case of a Small Autonomous Mobile Robot in an Office. ISCIS Emi Matsumoto, Michèle Sebag, Einoshin Suzuki
2010	A	`conf`	A mono surrogate for multiobjective optimization. GECCO Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2010	—	`conf`	A pareto-compliant surrogate approach for multiobjective optimization. GECCO (Companion) Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2010	—	`conf`	Adaptively detecting changes in Autonomic Grid Computing. GRID Xiangliang Zhang, Cécile Germain, Michèle Sebag
2010	J	`jnl`	Analyzing bandit-based adaptive operator selection mechanisms. Ann. Math. Artif. Intell. Álvaro Fialho, Luís Da Costa, Marc Schoenauer, Michèle Sebag
2010	—	`conf`	Building Portfolios for the Protein Structure Prediction Problem. WCB@ICLP Alejandro Arbelaez, Youssef Hamadi, Michèle Sebag
2010	—	`conf`	Comparison-Based Adaptive Strategy Selection with Bandits in Differential Evolution. PPSN (1) Álvaro Fialho, Raymond Ros, Marc Schoenauer, Michèle Sebag
2010	—	`conf`	Comparison-Based Optimizers Need Comparison-Based Surrogates. PPSN (1) Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2010	—	`conf`	Continuous Search in Constraint Programming. ICTAI (1) Alejandro Arbelaez, Youssef Hamadi, Michèle Sebag
2010	B	`conf`	Discovering Piecewise Linear Models of Grid Workload. CCGRID Tamás Éltetö, Cécile Germain-Renaud, Pascal Bondon, Michèle Sebag
2010	—	`conf`	Dominance-Based Pareto-Surrogate for Multi-Objective Optimization. SEAL Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
2010	A*	`conf`	Feature Selection as a One-Player Game. ICML Romaric Gaudel, Michèle Sebag
2010	—	`conf`	Fitness-AUC bandit adaptive strategy selection vs. the probability matching one within differential evolution: an empirical comparison on the bbob-2010 noiseless testbed. GECCO (Companion) Álvaro Fialho, Marc Schoenauer, Michèle Sebag
2010	—	`ch.`	Grammatical Inference. Encyclopedia of Machine Learning Lorenza Saitta, Michèle Sebag
2010	J	`jnl`	Guest editors' introduction: special issue of selected papers from ECML PKDD 2010. Data Min. Knowl. Discov. José L. Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag
2010	A*	`conf`	K-AP: Generating Specified K Clusters by Efficient Affinity Propagation. ICDM Xiangliang Zhang, Wei Wang, Kjetil Nørvåg, Michèle Sebag
2010	—	`ed.`	Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010, Proceedings, Part I ECML/PKDD (1) José L. Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag
2010	—	`ed.`	Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010, Proceedings, Part II ECML/PKDD (2) José L. Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag
2010	—	`ed.`	Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010, Proceedings, Part III ECML/PKDD (3) José L. Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag
2010	—	`ch.`	Nonstandard Criteria in Evolutionary Learning. Encyclopedia of Machine Learning Michèle Sebag
2010	—	`conf`	Open-Ended Evolutionary Robotics: An Information Theoretic Approach. PPSN (1) Pierre Delarboulas, Marc Schoenauer, Michèle Sebag
2010	J	`jnl`	Open-Ended Evolutionary Robotics: an Information Theoretic Approach CoRR Pierre Delarboulas, Marc Schoenauer, Michèle Sebag
2010	—	`ch.`	Phase Transitions in Machine Learning. Encyclopedia of Machine Learning Lorenza Saitta, Michèle Sebag
2010	J	`jnl`	Special issue for ECML PKDD 2010: Guest editors' introduction. Mach. Learn. José L. Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag
2010	—	`conf`	SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex system. NIPS Sylvain Chevallier, Hélène Paugam-Moisy, Michèle Sebag
2010	A	`conf`	Toward comparison-based adaptive operator selection. GECCO Álvaro Fialho, Marc Schoenauer, Michèle Sebag
2010	A	`conf`	Unsupervised Layer-Wise Model Selection in Deep Neural Networks. ECAI Ludovic Arnold, Hélène Paugam-Moisy, Michèle Sebag
2009	A	`conf`	Analysis of adaptive operator selection techniques on the royal road and long k-path problems. GECCO Álvaro Fialho, Marc Schoenauer, Michèle Sebag
2009	—	`conf`	Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm. ECML/PKDD (2) Philippe Rolet, Michèle Sebag, Olivier Teytaud
2009	—	`conf`	Dynamic Multi-Armed Bandits and Extreme Value-Based Rewards for Adaptive Operator Selection in Evolutionary Algorithms. LION Álvaro Fialho, Luís Da Costa, Marc Schoenauer, Michèle Sebag
2009	B	`conf`	Extreme compass and Dynamic Multi-Armed Bandits for Adaptive Operator Selection. IEEE Congress on Evolutionary Computation Jorge Maturana, Álvaro Fialho, Frédéric Saubion, Marc Schoenauer, Michèle Sebag
2009	—	`conf`	Extreme: dynamic multi-armed bandits for adaptive operator selection. GECCO (Companion) Álvaro Fialho, Luís Da Costa, Marc Schoenauer, Michèle Sebag
2009	B	`conf`	Memory-enhanced Evolutionary Robotics: The Echo State Network Approach. IEEE Congress on Evolutionary Computation Cédric Hartland, Nicolas Bredèche, Michèle Sebag
2009	B	`conf`	Multi-scale Real-Time Grid Monitoring with Job Stream Mining. CCGRID Xiangliang Zhang, Michèle Sebag, Cécile Germain-Renaud
2009	A	`conf`	Optimal robust expensive optimization is tractable. GECCO Philippe Rolet, Michèle Sebag, Olivier Teytaud
2009	J	`jnl`	Scaling Analysis of Affinity Propagation CoRR Cyril Furtlehner, Michèle Sebag, Xiangliang Zhang
2009	A*	`conf`	Toward autonomic grids: analyzing the job flow with affinity streaming. KDD Xiangliang Zhang, Cyril Furtlehner, Julien Perez, Cécile Germain-Renaud, Michèle Sebag
2008	J	`jnl`	A note on phase transitions and computational pitfalls of learning from sequences. J. Intell. Inf. Syst. Antoine Cornuéjols, Michèle Sebag
2008	A	`conf`	Adaptive operator selection with dynamic multi-armed bandits. GECCO Luís Da Costa, Álvaro Fialho, Marc Schoenauer, Michèle Sebag
2008	—	`conf`	Data Streaming with Affinity Propagation. ECML/PKDD (2) Xiangliang Zhang, Cyril Furtlehner, Michèle Sebag
2008	—	`conf`	Distributed and Incremental Clustering Based on Weighted Affinity Propagation. STAIRS Xiangliang Zhang, Cyril Furtlehner, Michèle Sebag
2008	J	`jnl`	DryadeParent, An Efficient and Robust Closed Attribute Tree Mining Algorithm. IEEE Trans. Knowl. Data Eng. Alexandre Termier, Marie-Christine Rousset, Michèle Sebag, Kouzou Ohara, Takashi Washio, Hiroshi Motoda
2008	A	`conf`	Extreme Value Based Adaptive Operator Selection. PPSN Álvaro Fialho, Luís Da Costa, Marc Schoenauer, Michèle Sebag
2008	—	`conf`	SoftwareTesting with Active Learning in a Graph. Evolutionary Test Generation Nicolas Baskiotis, Michèle Sebag, Marie-Claude Gaudel
2007	A*	`conf`	A Machine Learning Approach for Statistical Software Testing. IJCAI Nicolas Baskiotis, Michèle Sebag, Marie-Claude Gaudel, Sandrine-Dominique Gouraud
2007	B	`conf`	A Phase Transition-Based Perspective on Multiple Instance Kernels. ILP Romaric Gaudel, Michèle Sebag, Antoine Cornuéjols
2007	J	`jnl`	Ensemble Learning for Free with Evolutionary Algorithms ? CoRR Christian Gagné, Michèle Sebag, Marc Schoenauer, Marco Tomassini
2007	A	`conf`	Ensemble learning for free with evolutionary algorithms? GECCO Christian Gagné, Michèle Sebag, Marc Schoenauer, Marco Tomassini
2007	J	`jnl`	Evolving Symbolic Controllers CoRR Nicolas Godzik, Marc Schoenauer, Michèle Sebag
2007	—	`conf`	Structural Sampling for Statistical Software Testing. Probabilistic, Logical and Relational Learning - A Further Synthesis Nicolas Baskiotis, Michèle Sebag
2007	B	`conf`	Structural Statistical Software Testing with Active Learning in a Graph. ILP Nicolas Baskiotis, Michèle Sebag
2007	—	`conf`	Toward Behavioral Modeling of a Grid System: Mining the Logging and Bookkeeping Files. ICDM Workshops Xiangliang Zhang, Michèle Sebag, Cécile Germain
2006	J	`jnl`	Avoiding the Bloat with Stochastic Grammar-based Genetic Programming CoRR Alain Ratle, Michèle Sebag
2006	J	`jnl`	Functional Brain Imaging with Multi-Objective Multi-Modal Evolutionary Optimization CoRR Vojtech Krmicek, Michèle Sebag
2006	A	`conf`	Functional Brain Imaging with Multi-objective Multi-modal Evolutionary Optimization. PPSN Vojtech Krmicek, Michèle Sebag
2006	A	`conf`	Genetic Programming for Kernel-Based Learning with Co-evolving Subsets Selection. PPSN Christian Gagné, Marc Schoenauer, Michèle Sebag, Marco Tomassini
2006	J	`jnl`	Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection CoRR Christian Gagné, Marc Schoenauer, Michèle Sebag, Marco Tomassini
2006	J	`jnl`	Using Domain Knowledge in Evolutionary System Identification CoRR Marc Schoenauer, Michèle Sebag
2005	A*	`conf`	A Multi-Objective Multi-Modal Optimization Approach for Mining Stable Spatio-Temporal Patterns. IJCAI Michèle Sebag, Nicolas Tarrisson, Olivier Teytaud, Julien Lefèvre, Sylvain Baillet
2005	J	`jnl`	Artificial Agents and Speculative Bubbles CoRR Yann Semet, Sylvain Gelly, Marc Schoenauer, Michèle Sebag
2005	—	`conf`	Bayesian Learning with Local Support Vector Machines for Cancer Classification with Gene Expression Data. EvoWorkshops Elena Marchiori, Michèle Sebag
2005	A*	`conf`	Efficient Mining of High Branching Factor Attribute Trees. ICDM Alexandre Termier, Marie-Christine Rousset, Michèle Sebag, Kouzou Ohara, Takashi Washio, Hiroshi Motoda
2005	—	`conf`	From Factorial and Hierarchical HMM to Bayesian Network: A Representation Change Algorithm. SARA Sylvain Gelly, Nicolas Bredèche, Michèle Sebag
2005	—	`conf`	HMM hiérarchiques et factorisés: mécanisme d'inférence et apprentissage à partir de peu de données. CAP Sylvain Gelly, Nicolas Bredèche, Michèle Sebag
2005	—	`conf`	Inférence dans les HMM hiérarchiques et factorisés : changement de représentation vers le formalisme des Réseaux Bayésiens. EGC (Ateliers) Sylvain Gelly, Michèle Sebag, Nicolas Bredèche
2005	—	`conf`	Multi-objective Multi-modal Optimization for Mining Spatio-temporal Patterns. CAP Nicolas Tarrisson, Michèle Sebag, Olivier Teytaud, Julien Lefèvre, Sylvain Baillet
2005	A*	`conf`	Phase Transitions within Grammatical Inference. IJCAI Nicolas Pernot, Antoine Cornuéjols, Michèle Sebag
2005	—	`conf`	Phase transitions in grammatical inference. CAP Nicolas Pernot, Antoine Cornuéjols, Michèle Sebag
2005	J	`jnl`	Preference Learning in Terminology Extraction: A ROC-based approach CoRR Jérôme Azé, Mathieu Roche, Yves Kodratoff, Michèle Sebag
2005	—	`conf`	Systèmes inductifs-déductifs: une approche statistique. CAP Nicolas Baskiotis, Michèle Sebag, Olivier Teytaud
2004	A*	`conf`	C4.5 competence map: a phase transition-inspired approach. ICML Nicolas Baskiotis, Michèle Sebag
2004	A*	`conf`	DRYADE: A New Approach for Discovering Closed Frequent Trees in Heterogeneous Tree Databases. ICDM Alexandre Termier, Marie-Christine Rousset, Michèle Sebag
2004	—	`conf`	Ensemble Feature Ranking. PKDD Kees Jong, Jérémie Mary, Antoine Cornuéjols, Elena Marchiori, Michèle Sebag
2004	A	`conf`	Ensemble Learning with Evolutionary Computation: Application to Feature Ranking. PPSN Kees Jong, Elena Marchiori, Michèle Sebag
2004	J	`jnl`	Fast Theta-Subsumption with Constraint Satisfaction Algorithms. Mach. Learn. Jérôme Maloberti, Michèle Sebag
2004	C	`conf`	Feature selection in proteomic pattern data with support vector machines. CIBCB Kees Jong, Elena Marchiori, Michèle Sebag, Aad van der Vaart
2004	—	`conf`	Learning Interestingness Measures in Terminology Extraction. A ROC-based approach. ROCAI Mathieu Roche, Jérôme Azé, Yves Kodratoff, Michèle Sebag
2004	—	`conf`	Learning to Order Terms: Supervised Interestingness Measures in Terminology Extraction International Conference on Computational Intelligence Jérôme Azé, Mathieu Roche, Yves Kodratoff, Michèle Sebag
2004	A	`conf`	Robotics and Multi-agent Systems Robustness in the Long Run: Auto-teaching vs Anticipation in Evolutionary Robotics. PPSN Nicolas Godzik, Marc Schoenauer, Michèle Sebag
2003	—	`conf`	Evolving Symbolic Controllers. EvoWorkshops Nicolas Godzik, Marc Schoenauer, Michèle Sebag
2003	—	`conf`	Fouille de données visuelle et analyse de facteurs de risque médical. EGC Jérôme Azé, Noël Lucas, Michèle Sebag
2003	A*	`conf`	Impact Studies and Sensitivity Analysis in Medical Data Mining with ROC-based Genetic Learning. ICDM Michèle Sebag, Jérôme Azé, Noël Lucas
2003	—	`conf`	Nouveaux résultats en classification à l'aide d'un codage par motifs fréquents. EGC Sébastien Jouteau, Antoine Cornuéjols, Michèle Sebag, Philippe Tarroux, Jean-Sylvain Liénard
2003	—	`conf`	ROC-Based Evolutionary Learning: Application to Medical Data Mining. Artificial Evolution Michèle Sebag, Jérôme Azé, Noël Lucas
2003	J	`jnl`	Relational Learning as Search in a Critical Region. J. Mach. Learn. Res. Marco Botta, Attilio Giordana, Lorenza Saitta, Michèle Sebag
2003	J	`jnl`	Scalability and efficiency in multi-relational data mining. SIGKDD Explor. Hendrik Blockeel, Michèle Sebag
2002	B	`conf`	A Novel Approach to Machine Discovery: Genetic Programming and Stochastic Grammars. ILP Alain Ratle, Michèle Sebag
2002	J	`jnl`	Compact Unstructured Representations for Evolutionary Design. Appl. Intell. Hatem Hamda, François Jouve, Evelyne Lutton, Marc Schoenauer, Michèle Sebag
2002	A*	`conf`	Constraint-based Learning of Long Relational Concepts. ICML Jacques Ales Bianchetti, Céline Rouveirol, Michèle Sebag
2002	A*	`conf`	TreeFinder: a First Step towards XML Data Mining. ICDM Alexandre Termier, Marie-Christine Rousset, Michèle Sebag
2001	—	`conf`	Avoiding the Bloat with Stochastic Grammar-Based Genetic Programming. Artificial Evolution Alain Ratle, Michèle Sebag
2001	—	`conf`	Combining Statistics and Semantics for Word and Document Clustering. Workshop on Ontology Learning Alexandre Termier, Michèle Sebag, Marie-Christine Rousset
2001	J	`jnl`	Grammar-guided genetic programming and dimensional consistency: application to non-parametric identification in mechanics. Appl. Soft Comput. Alain Ratle, Michèle Sebag
2001	B	`ed.`	Inductive Logic Programming, 11th International Conference, ILP 2001, Strasbourg, France, September 9-11, 2001, Proceedings ILP Céline Rouveirol, Michèle Sebag
2001	B	`conf`	Theta-Subsumption in a Constraint Satisfaction Perspective. ILP Jérôme Maloberti, Michèle Sebag
2000	B	`conf`	A Distributed Resource Evolutionary Algorithm Machine (DREAM). CEC Ben Paechter, Thomas Bäck, Marc Schoenauer, Michèle Sebag, Ágoston E. Eiben, Juan Julián Merelo, Terence C. Fogarty
2000	A*	`conf`	Analyzing Relational Learning in the Phase Transition Framework. ICML Attilio Giordana, Lorenza Saitta, Michèle Sebag, Marco Botta
2000	J	`jnl`	Any-time Relational Reasoning: Resource-bounded Induction and Deduction Through Stochastic Matching. Mach. Learn. Michèle Sebag, Céline Rouveirol
2000	C	`conf`	Can Relational Learning Scale Up? ISMIS Attilio Giordana, Lorenza Saitta, Michèle Sebag, Marco Botta
2000	A	`conf`	Genetic Programming and Domain Knowledge: Beyond the Limitations of Grammar-Guided Machine Discovery. PPSN Alain Ratle, Michèle Sebag
1999	A*	`conf`	Constructive Induction: A Version Space-based Approach. IJCAI Michèle Sebag
1999	B	`conf`	From first order logic to Nd: a data driven reformulation. ESANN Michèle Sebag
1999	J	`jnl`	Hacia un Enfoque General del Trazado de Grafos. Inteligencia Artif. Alejandro Rosete-Suárez, Alberto Nogueira-Keeling, Alberto Ochoa-Rodríguez, Michèle Sebag
1999	—	`conf`	Relational Learning: Hard Problems and Phase Transitions. AI*IA Marco Botta, Attilio Giordana, Lorenza Saitta, Michèle Sebag
1998	B	`conf`	A Stochastic Simple Similarity. ILP Michèle Sebag
1998	—	`conf`	Continuous Mimetic Evolution. ECML Antoine Ducoulombier, Michèle Sebag
1998	A	`conf`	Extending Population-Based Incremental Learning to Continuous Search Spaces. PPSN Michèle Sebag, Antoine Ducoulombier
1998	J	`jnl`	Revisiting the Memory of Evolution. Fundam. Informaticae Michèle Sebag, Marc Schoenauer, Mathieu Peyral
1998	J	`jnl`	Twelve Numerical, Symbolic and Hybrid Supervised Classification Methods. Int. J. Pattern Recognit. Artif. Intell. Olivier Gascuel, Bernadette Bouchon-Meunier, Gilles Caraux, Patrick Gallinari, Alain Guénoche, Yann Guermeur, Yves Lechevallier, Christophe Marsala, Laurent Miclet, Jacques Nicolas, Richard Nock, Mohammed Ramdani, Michèle Sebag, Basavanneppa Tallur, Gilles Venturini, Patrick Vitte
1997	C	`conf`	A society of hill-climbers. ICEC Michèle Sebag, Marc Schoenauer
1997	B	`conf`	Distance Induction in First Order Logic. ILP Michèle Sebag
1997	—	`conf`	Inductive Learning of Mutation Step-Size in Evolutionary Parameter Optimization. Evolutionary Programming Michèle Sebag, Marc Schoenauer, Caroline Ravise
1997	—	`conf`	Mimetic Evolution. Artificial Evolution Mathieu Peyral, Antoine Ducoulombier, Caroline Ravise, Marc Schoenauer, Michèle Sebag
1997	—	`conf`	Toward Civilized Evolution: Developing Inhibitions. ICGA Michèle Sebag, Marc Schoenauer, Caroline Ravise
1997	—	`conf`	Tractable Induction and Classification in First Order Logic Via Stochastic Matching. IJCAI (2) Michèle Sebag, Céline Rouveirol
1996	A*	`conf`	An Advanced Evolution Should Not Repeat its Past Errors. ICML Caroline Ravise, Michèle Sebag
1996	—	`conf`	Controlling Evolution by Means of Machine Learning. Evolutionary Programming Michèle Sebag, Caroline Ravise, Marc Schoenauer
1996	A*	`conf`	Delaying the Choice of Bias: A Disjunctive Version Space Approach. ICML Michèle Sebag
1996	—	`conf`	Induction of Constraint Logic Programs. PRICAI Workshops Michèle Sebag, Céline Rouveirol, Jean-Francois Puget
1996	A	`conf`	Mutation by Imitation in Boolean Evolution Strategies. PPSN Michèle Sebag, Marc Schoenauer
1996	B	`conf`	Polynomial-Time Learning in Logic Programming and Constraint Logic Programming. Inductive Logic Programming Workshop Michèle Sebag, Céline Rouveirol
1995	J	`jnl`	A numerical strategy to defectuous knowledge using. Ann. Oper. Res. Michèle Sebag, Marc Schoenauer
1995	—	`conf`	An Induction-based Control for Genetic Algorithms (Extended Abstract). ECML Michèle Sebag, Marc Schoenauer, Caroline Ravise
1995	—	`conf`	Induction-Based Control of Genetic Algorithms. Artificial Evolution Caroline Ravise, Michèle Sebag, Marc Schoenauer
1994	A*	`conf`	A Constraint-based Induction Algorithm in FOL. ICML Michèle Sebag
1994	A	`conf`	Controlling Crossover through Inductive Learning. PPSN Michèle Sebag, Marc Schoenauer
1994	—	`conf`	Using Constraints to Building Version Spaces. ECML Michèle Sebag
1993	—	`conf`	A Rule-Based Similarity Measure. EWCBR Michèle Sebag, Marc Schoenauer
1992	A	`conf`	Learning to Control Inconsistent Knowledge. ECAI Michèle Sebag, Marc Schoenauer
1991	—	`conf`	Using Examples to Refine a Redundant Knowledge Base. EUROVAV Michèle Sebag, Marc Schoenauer
1990	—	`conf`	Incremental Learning of Rules and Meta-rules. ML Marc Schoenauer, Michèle Sebag