Michèle Sebag

Publication Activity (10 Years)

Years Active: 1990-2024
Publications (10 Years): 46

Top Venues

CoRR

ECML/PKDD (1)

IJCAI

ICLR

Publications

Audrey Poinsot, Alessandro Leite, Nicolas Chesneau, Michèle Sebag, Marc Schoenauer
Learning Structural Causal Models through Deep Generative Models: Methods, Guarantees, and Challenges. CoRR (2024)
Shuyu Dong, Michèle Sebag, Kento Uemura, Akito Fujii, Shuang Chang, Yusuke Koyanagi, Koji Maruhashi
DCDILP: a distributed learning method for large-scale causal structure learning. CoRR (2024)
Guillaume Bied, Solal Nathan, Elia Perennes, Morgane Hoffmann, Philippe Caillou, Bruno Crépon, Christophe Gaillac, Michèle Sebag
Toward Job Recommendation for All. IJCAI (2023)
Guillaume Bied, Elia Perennes, Solal Nathan, Victor Naya, Philippe Caillou, Bruno Crépon, Christophe Gaillac, Michèle Sebag
RECTO : REcommandation diminuant la Congestion par Transport Optimal. APIA (2023)
Guillaume Bied, Christophe Gaillac, Morgane Hoffmann, Philippe Caillou, Bruno Crépon, Solal Nathan, Michèle Sebag
Fairness in job recommendations: estimating, explaining, and reducing gender gaps. AEQUITAS@ECAI (2023)
Alice Lacan, Michèle Sebag, Blaise Hanczar
GAN-based data augmentation for transcriptomics: survey and comparative assessment. Bioinform. 39 (Supplement-1) (2023)
Shuyu Dong, Kento Uemura, Akito Fujii, Shuang Chang, Yusuke Koyanagi, Koji Maruhashi, Michèle Sebag
High-Dimensional Causal Discovery: Learning from Inverse Covariance via Independence-based Decomposition. CoRR (2022)
Shuyu Dong, Michèle Sebag
From graphs to DAGs: a low-complexity model and a scalable algorithm. CoRR (2022)
Diviyan Kalainathan, Olivier Goudet, Isabelle Guyon, David Lopez-Paz, Michèle Sebag
Structural Agnostic Modeling: Adversarial Learning of Causal Graphs. J. Mach. Learn. Res. 23 (2022)
Herilalaina Rakotoarison, Louisot Milijaona, Andry Rasoanaivo, Michèle Sebag, Marc Schoenauer
Learning meta-features for AutoML. ICLR (2022)
Shuyu Dong, Michèle Sebag
From Graphs to DAGs: A Low-Complexity Model and a Scalable Algorithm. ECML/PKDD (5) (2022)
Philippe Caillou, Jonas Renault, Jean-Daniel Fekete, Anne-Catherine Letournel, Michèle Sebag
Cartolabe: A Web-Based Scalable Visualization of Large Document Collections. IEEE Computer Graphics and Applications 41 (2) (2021)
Ksenia Gasnikova, Olivier Allais, Michèle Sebag
Towards causal modeling of nutritional outcomes. CAWS (2021)
Omar Shrit, Michèle Sebag
I2SL: Learn How to Swarm Autonomous Quadrotors Using Iterative Imitation Supervised Learning. EPIA (2021)
Roman Bresson, Johanne Cohen, Eyke Hüllermeier, Christophe Labreuche, Michèle Sebag
On the Identifiability of Hierarchical Decision Models. KR (2021)
Mikhail Evchenko, Joaquin Vanschoren, Holger H. Hoos, Marc Schoenauer, Michèle Sebag
Frugal Machine Learning. CoRR (2021)
Omar Shrit, David Filliat, Michèle Sebag
Iterative Learning for Model Reactive Control: Application to Autonomous Multi-agent Control. ICARA (2021)
Erich Kummerfeld, Thomas Woolf, Will Glad, Michèle Sebag, Sisi Ma
Important Topics in Causal Analysis: Summary of the CAWS 2021 Round Table Discussion. CAWS (2021)
Victor Berger, Michèle Sebag
Boltzmann Tuning of Generative Models. CoRR (2021)
Victor Berger, Michèle Sebag
Variational Auto-Encoder: not all failures are equal. CoRR (2020)
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
Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities. Frontiers Big Data 3 (2020)
Victor Berger, Michèle Sebag
From abstract items to latent spaces to observed data and back: Compositional Variational Auto-Encoder. CoRR (2020)
Philippe Caillou, Jonas Renault, Jean-Daniel Fekete, Anne-Catherine Letournel, Michèle Sebag
Cartolabe: A Web-Based Scalable Visualization of Large Document Collections. CoRR (2020)
Mandar Chandorkar, Cyril Furtlehner, Bala Poduval, Enrico Camporeale, Michèle Sebag
Dynamic Time Lag Regression: Predicting What & When. ICLR (2020)
Gwendoline de Bie, Herilalaina Rakotoarison, Gabriel Peyré, Michèle Sebag
Distribution-Based Invariant Deep Networks for Learning Meta-Features. CoRR (2020)
Roman Bresson, Johanne Cohen, Eyke Hüllermeier, Christophe Labreuche, Michèle Sebag
Neural Representation and Learning of Hierarchical 2-additive Choquet Integrals. IJCAI (2020)
Herilalaina Rakotoarison, Marc Schoenauer, Michèle Sebag
Automated Machine Learning with Monte-Carlo Tree Search (Extended Version). CoRR (2019)
Herilalaina Rakotoarison, Marc Schoenauer, Michèle Sebag
Automated Machine Learning with Monte-Carlo Tree Search. IJCAI (2019)
Jorge G. Madrid, Hugo Jair Escalante, Eduardo F. Morales, Wei-Wei Tu, Yang Yu, Lisheng Sun-Hosoya, Isabelle Guyon, Michèle Sebag
Towards AutoML in the presence of Drift: first results. CoRR (2019)
Victor Berger, Michèle Sebag
From Abstract Items to Latent Spaces to Observed Data and Back: Compositional Variational Auto-Encoder. ECML/PKDD (1) (2019)
Alice Schoenauer Sebag, Louise Heinrich, Marc Schoenauer, Michèle Sebag, Lani F. Wu, Steven J. Altschuler
Multi-Domain Adversarial Learning. ICLR (Poster) (2019)
Alice Schoenauer Sebag, Louise Heinrich, Marc Schoenauer, Michèle Sebag, Lani F. Wu, Steven J. Altschuler
Multi-Domain Adversarial Learning. CoRR (2019)
Guillaume Doquet, Michèle Sebag
Agnostic Feature Selection. ECML/PKDD (1) (2019)
Lisheng Sun-Hosoya, Isabelle Guyon, Michèle Sebag
ActivMetal: Algorithm Recommendation with Active Meta Learning. IAL@PKDD/ECML (2018)
Yoann Isaac, Quentin Barthelemy, Cédric Gouy-Pailler, Michèle Sebag, Jamal Atif
Multi-dimensional signal approximation with sparse structured priors using split Bregman iterations. Signal Process. 130 (2017)
Mustafa Misir, Michèle Sebag
Alors: An algorithm recommender system. Artif. Intell. 244 (2017)
François Gonard, Marc Schoenauer, Michèle Sebag
ASAP.V2 and ASAP.V3: Sequential optimization of an Algorithm Selector and a Scheduler. OASC (2017)
Thomas Schmitt, François Gonard, Phillipe Caillou, Michèle Sebag
Language Modelling for Collaborative Filtering: Application to Job Applicant Matching. ICTAI (2017)
Olivier Bousquet, Sylvain Gelly, Karol Kurach, Marc Schoenauer, Michèle Sebag, Olivier Teytaud, Damien Vincent
Toward Optimal Run Racing: Application to Deep Learning Calibration. CoRR (2017)
Alice Schoenauer Sebag, Marc Schoenauer, Michèle Sebag
Stochastic Gradient Descent: Going As Fast As Possible But Not Faster. CoRR (2017)
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
A brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning without Human Intervention. AutoML@ICML (2016)
Michèle Sebag, Riad Akrour, Basile Mayeur, Marc Schoenauer
Anti Imitation-Based Policy Learning. ECML/PKDD (2) (2016)
Thomas Schmitt, Phillipe Caillou, Michèle Sebag
Matching Jobs and Resumes: a Deep Collaborative Filtering Task. GCAI (2016)
Yoann Isaac, Quentin Barthelemy, Cédric Gouy-Pailler, Michèle Sebag, Jamal Atif
Multi-dimensional signal approximation with sparse structured priors using split Bregman iterations. CoRR (2016)
Masaharu Yoshioka, Masahiko Itoh, Michèle Sebag
Interactive Metric Learning-Based Visual Data Exploration: Application to the Visualization of a Scientific Social Network. ISIP (2015)
Michèle Sebag
Collaborative Algorithm Platforms. DATA (2015)
Nicolas Galichet, Michèle Sebag, Olivier Teytaud
Exploration vs Exploitation vs Safety: Risk-averse Multi-Armed Bandits. CoRR (2014)
Guohua Zhang, Michèle Sebag
Coupling Evolution and Information Theory for Autonomous Robotic Exploration. PPSN (2014)
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
Strategic Choices in Optimization. J. Inf. Sci. Eng. 30 (3) (2014)
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag, Nikolaus Hansen
Maximum Likelihood-Based Online Adaptation of Hyper-Parameters in CMA-ES. PPSN (2014)
Artémis Llamosi, Adel Mezine, Florence d'Alché-Buc, Véronique Letort, Michèle Sebag
Experimental Design in Dynamical System Identification: A Bandit-Based Active Learning Approach. ECML/PKDD (2) (2014)
Xiangliang Zhang, Cyril Furtlehner, Cécile Germain-Renaud, Michèle Sebag
Data Stream Clustering With Affinity Propagation. IEEE Trans. Knowl. Data Eng. 26 (7) (2014)
Joel Ribeiro, Josep Carmona, Mustafa Misir, Michèle Sebag
A Recommender System for Process Discovery. BPM (2014)
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag, Nikolaus Hansen
Maximum Likelihood-based Online Adaptation of Hyper-parameters in CMA-ES. CoRR (2014)
Marc Schoenauer, Riad Akrour, Michèle Sebag, Jean-Christophe Souplet
Programming by Feedback. ICML (2014)
Blaise Hanczar, Michèle Sebag
Combination of One-Class Support Vector Machines for Classification with Reject Option. ECML/PKDD (1) (2014)
Luc De Raedt, Siegfried Nijssen, Barry O'Sullivan, Michèle Sebag
Constraints, Optimization and Data (Dagstuhl Seminar 14411). Dagstuhl Reports 4 (10) (2014)
Michèle Sebag
A tour of machine learning: An AI perspective. AI Commun. 27 (1) (2014)
Yoann Isaac, Quentin Barthelemy, Jamal Atif, Cédric Gouy-Pailler, Michèle Sebag
Multi-dimensional sparse structured signal approximation using split bregman iterations. ICASSP (2013)
Weijia Wang, Michèle Sebag
Hypervolume indicator and dominance reward based multi-objective Monte-Carlo Tree Search. Mach. Learn. 92 (2-3) (2013)
Manuel Loth, Michèle Sebag, Youssef Hamadi, Marc Schoenauer, Christian Schulte
Hybridizing Constraint Programming and Monte-Carlo Tree Search: Application to the Job Shop Problem. LION (2013)
Rémi Bardenet, Mátyás Brendel, Balázs Kégl, Michèle Sebag
Collaborative hyperparameter tuning. ICML (2) (2013)
François-Michel De Rainville, Michèle Sebag, Christian Gagné, Marc Schoenauer, Denis Laurendeau
Sustainable cooperative coevolution with a multi-armed bandit. GECCO (2013)
Manuel Loth, Michèle Sebag, Youssef Hamadi, Marc Schoenauer
Bandit-Based Search for Constraint Programming. CP (2013)
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
Bi-population CMA-ES agorithms with surrogate models and line searches. GECCO (Companion) (2013)
Shigeru Takano, Ilya Loshchilov, David Meunier, Michèle Sebag, Einoshin Suzuki
Fast Adaptive Object Detection towards a Smart Environment by a Mobile Robot. AmI (2013)
Nicolas Galichet, Michèle Sebag, Olivier Teytaud
Exploration vs Exploitation vs Safety: Risk-Aware Multi-Armed Bandits. ACML (2013)
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
Intensive surrogate model exploitation in self-adaptive surrogate-assisted cma-es (saacm-es). GECCO (2013)
François-Michel De Rainville, Michèle Sebag, Christian Gagné, Marc Schoenauer, Denis Laurendeau
Sustainable Cooperative Coevolution with a Multi-Armed Bandit CoRR (2013)
Yoann Isaac, Quentin Barthelemy, Jamal Atif, Cédric Gouy-Pailler, Michèle Sebag
Multi-dimensional sparse structured signal approximation using split Bregman iterations CoRR (2013)
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
KL-based Control of the Learning Schedule for Surrogate Black-Box Optimization. CoRR (2013)
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
Self-Adaptive Surrogate-Assisted Covariance Matrix Adaptation Evolution Strategy CoRR (2012)
Riad Akrour, Marc Schoenauer, Michèle Sebag
APRIL: Active Preference-learning based Reinforcement Learning CoRR (2012)
Thomas Philip Runarsson, Marc Schoenauer, Michèle Sebag
Pilot, Rollout and Monte Carlo Tree Search Methods for Job Shop Scheduling CoRR (2012)
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
Black-box optimization benchmarking of IPOP-saACM-ES and BIPOP-saACM-ES on the BBOB-2012 noiseless testbed. GECCO (Companion) (2012)
Michèle Sebag, Olivier Teytaud
Upper Confidence Tree-Based Consistent Reactive Planning Application to MineSweeper. LION (2012)
Thomas Philip Runarsson, Marc Schoenauer, Michèle Sebag
Pilot, Rollout and Monte Carlo Tree Search Methods for Job Shop Scheduling. LION (2012)
Sylvain Gelly, Levente Kocsis, Marc Schoenauer, Michèle Sebag, David Silver, Csaba Szepesvári, Olivier Teytaud
The grand challenge of computer Go: Monte Carlo tree search and extensions. Commun. ACM 55 (3) (2012)
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
Alternative Restart Strategies for CMA-ES. PPSN (1) (2012)
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
Black-box optimization benchmarking of IPOP-saACM-ES on the BBOB-2012 noisy testbed CoRR (2012)
Riad Akrour, Marc Schoenauer, Michèle Sebag
APRIL: Active Preference Learning-Based Reinforcement Learning. ECML/PKDD (2) (2012)
Tianshi Chen, Yunji Chen, Marc Duranton, Qi Guo, Atif Hashmi, Mikko H. Lipasti, Andrew Nere, Shi Qiu, Michèle Sebag, Olivier Temam
BenchNN: On the broad potential application scope of hardware neural network accelerators. IISWC (2012)
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
Black-box optimization benchmarking of IPOP-saACM-ES and BIPOP-saACM-ES on the BBOB-2012 noiseless testbed CoRR (2012)
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
Black-box optimization benchmarking of IPOP-saACM-ES on the BBOB-2012 noisy testbed. GECCO (Companion) (2012)
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
Black-box optimization benchmarking of NIPOP-aCMA-ES and NBIPOP-aCMA-ES on the BBOB-2012 noiseless testbed. GECCO (Companion) (2012)
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
Alternative Restart Strategies for CMA-ES CoRR (2012)
Weijia Wang, Michèle Sebag
Multi-objective Monte-Carlo Tree Search. ACML (2012)
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
Self-adaptive surrogate-assisted covariance matrix adaptation evolution strategy. GECCO (2012)
Tamás Éltetö, Cécile Germain-Renaud, Pascal Bondon, Michèle Sebag
Towards Non-Stationary Grid Models. J. Grid Comput. 9 (4) (2011)
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
Not All Parents Are Equal for MO-CMA-ES. EMO (2011)
David Meunier, Michèle Sebag, Shin Ando
Characterizing Anomalous Behaviors and Revising Robotic Controllers. ICDM Workshops (2011)
Sylvain Chevallier, Nicolas Bredèche, Hélène Paugam-Moisy, Michèle Sebag
Emergence of temporal and spatial synchronous behaviors in a foraging swarm. ECAL (2011)
Riad Akrour, Marc Schoenauer, Michèle Sebag
Preference-Based Policy Learning. ECML/PKDD (1) (2011)
Cédric Gouy-Pailler, Michèle Sebag, Anthony Larue, Antoine Souloumiac
Single trial variability in brain-computer interfaces based on motor imagery: Learning in the presence of labeling noise. Int. J. Imaging Syst. Technol. 21 (2) (2011)
Cécile Germain-Renaud, Alain Cady, Philippe Gauron, Michel Jouvin, Charles Loomis, Janusz Martyniak, Julien Nauroy, Guillaume Philippon, Michèle Sebag
The Grid Observatory. CCGRID (2011)
Adrien Couëtoux, Mario Milone, Mátyás Brendel, Hassen Doghmen, Michèle Sebag, Olivier Teytaud
Continuous RAVE. ACML (2011)
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
Adaptive coordinate descent. GECCO (2011)
Emi Matsumoto, Michèle Sebag, Einoshin Suzuki
Using SVM to Avoid Humans: A Case of a Small Autonomous Mobile Robot in an Office. ISCIS (2011)
Asuki Kouno, Jean-Marc Montanier, Shigeru Takano, Nicolas Bredèche, Marc Schoenauer, Michèle Sebag, Einoshin Suzuki
On-Board Evolutionary Algorithm and Off-Line Rule Discovery for Column Formation in Swarm Robotics. IAT (2011)
José L. Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag
Guest editors' introduction: special issue of selected papers from ECML PKDD 2010. Data Min. Knowl. Discov. 21 (2) (2010)

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Publication Activity (10 Years)

Top Topics

Top Venues

Michèle Sebag