Michèle Sebag
Revision as of 20:24, 12 September 2019 by GerdIsenberg (talk | contribs) (Created page with "'''Home * People * Michèle Sebag''' FILE:micsebag.jpg|border|right|thumb|link=https://www.lri.fr/~sebag/| Michèle Sebag <ref>[https://www.lri.fr/~sebag...")
Michèle Sebag [1]
Michèle Sebag,
a French mathematician and computer scientist, head of Laboratoire de Recherche en Informatique, LRI, French National Centre for Scientific Research, CNRS, Paris-Sud 11 University,
and along with Marc Schoenauer head the TAO Project Team [2], National Institute for Research in Computer Science and Control, INRIA, Saclay, Île-de-France.
Her research interests include the broad range of artificial intelligence, machine learning, knowledge discovery, stochastic optimization and genetic programming [3].
Selected Publications
1990 ...
- Michèle Sebag (1990). A symbolic-numerical approach for supervised learning from examples and rules. Ph.D. thesis, Paris Dauphine University
- Marc Schoenauer, Michèle Sebag (1990). Incremental Learning of Rules and Meta-rules. ML 1990
- Michèle Sebag, Marc Schoenauer (1992). Learning to Control Inconsistent Knowledge. ECAI 1992
- Michèle Sebag (1997). Stochastic Heuristics for Machine Learning & Machine Learning for Stochastic Optimization. Habilitation, Paris-Sud 11 University
2000 ...
- Céline Rouveirol, Michèle Sebag (eds.) (2001). Inductive Logic Programming - 11th International Conference, ILP 2001 Strasbourg, France, September 9–11, 2001 Proceedings. Lecture Notes in Computer Science, Vol. 2157, Springer
- Jérôme Maloberti, Michèle Sebag (2001). θ-Subsumption in a Constraint Satisfaction Perspective. ILP 2001
- Sylvain Gelly, Nicolas Bredèche, Michèle Sebag (2005). From Factorial and Hierarchical HMM to Bayesian Network : A Representation Change Algorithm. Proceedings of the Symposium on Abstraction, Reformulation and Approximation 2005, p107-120 (SARA 2005). Lecture Notes in Computer Science, Vol. 3607
- Marc Schoenauer, Michèle Sebag (2006). Using Domain Knowledge in Evolutionary System Identification. arXiv:cs/0602021
2010 ...
- Romaric Gaudel, Michèle Sebag (2010). Feature Selection as a one-player game. ICML 2010, pdf
- Sylvain Gelly, Marc Schoenauer, Michèle Sebag, Olivier Teytaud, Levente Kocsis, David Silver, Csaba Szepesvári (2012). The Grand Challenge of Computer Go: Monte Carlo Tree Search and Extensions. Communications of the ACM, Vol. 55, No. 3, pdf preprint
- Ilya Loshchilov, Marc Schoenauer, Michèle Sebag (2012). Alternative Restart Strategies for CMA-ES. arXiv:1207.0206 [7]
- Thomas Philip Runarsson, Marc Schoenauer, Michèle Sebag (2012). Pilot, Rollout and Monte Carlo Tree Search Methods for Job Shop Scheduling. arXiv:1210.0374
- Ilya Loshchilov, Marc Schoenauer, Michèle Sebag (2013). KL-based Control of the Learning Schedule for Surrogate Black-Box Optimization. arXiv:1308.2655
- Olivier Bousquet, Sylvain Gelly, Karol Kurach, Marc Schoenauer, Michèle Sebag, Olivier Teytaud, Damien Vincent (2017). Toward Optimal Run Racing: Application to Deep Learning Calibration. arXiv:1706.03199
- Alice Schoenauer-Sebag, Marc Schoenauer, Michèle Sebag (2017). Stochastic Gradient Descent: Going As Fast As Possible But Not Faster. arXiv:1709.01427
- Herilalaina Rakotoarison, Marc Schoenauer, Michèle Sebag (2019). Automated Machine Learning with Monte-Carlo Tree Search. arXiv:1906.00170
External Links
- Home page of Michele Sebag
- Michèle Sebag - University of Paris-Sud 11 - videolectures.net
- Michèle Sebag - Algorithm Selection and Configuration with Monte-Carlo Tree Search, WiDS Zürich 2019: Keynote, YouTube Video
