Michèle Sebag

Martine-Michèle Sebag is a French computer scientist, primarily focused on machine learning. She has over 6,000 citations.[1]

Sebag studied mathematics at the Ecole Normale Supérieure, and later worked in the computer science industry, starting at Thomson Corporation,[2] where she was introduced to artificial intelligence. She then moved into 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.[3]

She was named chevalier of the Légion d'honneur in 2019.[4]

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.
gollark: I mean, unless you have specific glibc-uous requirements.
gollark: It is somewhat better, though.
gollark: HTTP/3 is that over QUIC, which in theory allows performance gains.
gollark: HTTP/2 is over TCP but multiplexed fancily and supported basically everywhere.
gollark: My website supported HTTP/3 for quite a while via a very non-production-ready experimental nginx because shiny new technology, until it turned out that apparently it was broken in Chrome somehow.

References
  1. "Michèle Sebag". Google Scholar. Retrieved 18 August 2019.
  2. "Chercheuse tout-terrain : Michèle Sebag, responsable de l'équipe apprentissage et optimisation du LRI-CNRS". L'usine nouvelle. Retrieved 18 August 2019.
  3. "Michele Sebag". Laboratoire de Recherche en Informatique (LRI). Université Paris-Sud. Retrieved 18 August 2019.
  4. Mourgere, Isabelle. "Légion d'honneur du 1er janvier 2019 : une promotion sous l'ère de la parité". TV5Monde. Retrieved 18 August 2019.
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