PK650: Article on French AI computer scientist.
[[File:Michèle Sebag.jpg|thumb]]
Martine-Michèle Sebag is a French computer scientist, primarily focused on [[machine learning]]. She has over 6,000 citations.<ref></ref>
Michèle studied mathematics at the [[Ecole Normale Supérieure]], and later worked in the computer science industry, starting at [[Thomson Corporation]],<ref></ref> where she was introduced to artificial intelligence. She then moven on to the research field, at the Laboratoire de Mécanique des Solides at [[Ecole Polytechnique]].
She was awarded a PhD from the [[University of Paris-Sud]], [[Paris Dauphine University]] and Ecole Polytechnique. Sebag started work at the [[Centre national de la recherche scientifique]] (CNRS) as a research fellow in 1991.
Sebag is deputy director of the Laboratoire de Recherche en Informatique at the CNRS; Head of group A-O at the latter; co-head of Projet TAO at INRIA Saclay; and principal scientist at the CNRS.<ref></ref>
She was named chevalier of the [[Légion d'honneur]] in 2019.<ref></ref>
==Selected research==
*Gelly, Sylvain, et al. "The grand challenge of computer Go: Monte Carlo tree search and extensions." Communications of the ACM 55.3 (2012): 106-113.
*Bordes, Antoine, Léon Bottou, and Patrick Gallinari. "SGD-QN: Careful quasi-Newton stochastic gradient descent." Journal of Machine Learning Research 10.Jul (2009): 1737-1754.
*Termier, Alexandre, M-C. Rousset, and Michèle Sebag. "Treefinder: a first step towards xml data mining." 2002 IEEE International Conference on Data Mining, 2002. Proceedings.. IEEE, 2002.
*Sebag, Michèle, and Antoine Ducoulombier. "Extending population-based incremental learning to continuous search spaces." International Conference on Parallel Problem Solving from Nature. Springer, Berlin, Heidelberg, 1998.
==Further reading==
*José L. Balcázar; Francesco Bonchi; Aristides Gionis; 2010. Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010. Proceedings. Springer. ISBN 978-3-642-15939-8.
*Taras Kowaliw; Nicolas Bredeche; René Doursat; 2014. Growing Adaptive Machines: Combining Development and Learning in Artificial Neural Networks. Springer. ISBN 978-3-642-55337-0.
==References==
==External links==
*[https://ift.tt/2OPIpO1 article by Sebag in Le Monde]
Martine-Michèle Sebag is a French computer scientist, primarily focused on [[machine learning]]. She has over 6,000 citations.<ref></ref>
Michèle studied mathematics at the [[Ecole Normale Supérieure]], and later worked in the computer science industry, starting at [[Thomson Corporation]],<ref></ref> where she was introduced to artificial intelligence. She then moven on to the research field, at the Laboratoire de Mécanique des Solides at [[Ecole Polytechnique]].
She was awarded a PhD from the [[University of Paris-Sud]], [[Paris Dauphine University]] and Ecole Polytechnique. Sebag started work at the [[Centre national de la recherche scientifique]] (CNRS) as a research fellow in 1991.
Sebag is deputy director of the Laboratoire de Recherche en Informatique at the CNRS; Head of group A-O at the latter; co-head of Projet TAO at INRIA Saclay; and principal scientist at the CNRS.<ref></ref>
She was named chevalier of the [[Légion d'honneur]] in 2019.<ref></ref>
==Selected research==
*Gelly, Sylvain, et al. "The grand challenge of computer Go: Monte Carlo tree search and extensions." Communications of the ACM 55.3 (2012): 106-113.
*Bordes, Antoine, Léon Bottou, and Patrick Gallinari. "SGD-QN: Careful quasi-Newton stochastic gradient descent." Journal of Machine Learning Research 10.Jul (2009): 1737-1754.
*Termier, Alexandre, M-C. Rousset, and Michèle Sebag. "Treefinder: a first step towards xml data mining." 2002 IEEE International Conference on Data Mining, 2002. Proceedings.. IEEE, 2002.
*Sebag, Michèle, and Antoine Ducoulombier. "Extending population-based incremental learning to continuous search spaces." International Conference on Parallel Problem Solving from Nature. Springer, Berlin, Heidelberg, 1998.
==Further reading==
*José L. Balcázar; Francesco Bonchi; Aristides Gionis; 2010. Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010. Proceedings. Springer. ISBN 978-3-642-15939-8.
*Taras Kowaliw; Nicolas Bredeche; René Doursat; 2014. Growing Adaptive Machines: Combining Development and Learning in Artificial Neural Networks. Springer. ISBN 978-3-642-55337-0.
==References==
==External links==
*[https://ift.tt/2OPIpO1 article by Sebag in Le Monde]
from Wikipedia - New pages [en] https://ift.tt/31OqybP
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