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Research Area: Machine Learning |
Profile
Olivier Chapelle is a research scientist in the machine learning group of Yahoo! Research.
He graduated in theoretical computer science from the Ecole Normale Supérieure de Lyon in 1999. From 1998 he has been working in AT&T Labs with V. Vapnik on Support Vector Machines and regularization theory. In 2002, he received a doctorate from the University of Paris 6 in the field of learning theory with advisors Vladimir Vapnik and Patrick Gallinari. He then pursued a post-doc at the Max Planck Institute in Tübingen where he worked on semi-supervised learning and kernel machines.
Since joining Yahoo! Research in 2006, Dr Chapelle has mostly been working on learning to rank.
He is associate editor for PAMI, the #1 IEEE journal in computer science.
Recent Publications, Projects and News
- Early exit optimizations for additive machine learned ranking systems B.B. Cambazoglu; H. Zaragoza; O. Chapelle; J. Chen; C. Liao; Z. Zheng; J. Degenhardt, The Third International Conference on Web Search and Web Data Mining, 2010 [view abstract]
- Expected Reciprocal Rank for Graded Relevance Olivier Chapelle; Donald Metzler; Ya Zhang; Pierre Grinspan, Conference on Information and Knowledge Management (CIKM), 2009 [view abstract]
- Estimating Predictive Variances with Kernel Ridge Regression Cawley, G. C. ; Talbot, N. L.C. ; Chapelle, O., Lecture Notes in Computer Science ; 3944, Springer, 2006