Cécile Levasseur

Education

I received the M.S./Dipl.Ing. degree in Communication Systems from the Swiss Federal Institute of Technology Lausanne (EPFL) in 2002, and the M.S. and Ph.D. degrees in Electrical Engineering from the University of California, San Diego (UCSD) respectively in 2004 and September 2009.

Research Interests

Machine Learning, Statistical Pattern Recognition, Data Mining.

My Ph.D. thesis, "Generalized Linear Statistics for Mixed Exponential Families", studies the problem of learning the underlying statistical structure of complex data sets for both supervised and unsupervised data-driven decision making purposes and, using exponential family properties, establishes a new unified theoretical model called Generalized Linear Statistics (GLS).

Publications

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Data-Pattern Discovery Methods for Detection in Nongaussian High-dimensional Data Sets (with K. Kreutz-Delgado, U. F. Mayer and G. Gancarz). Conference Record of the Thirty-Ninth Asilomar Conference on Signals, Systems and Computers, pp. 545-549, Nov. 2005.
Generalized Statistical Methods for Unsupervised Minority Class Detection in Mixed Data Sets (with U. F. Mayer, B. Burdge and K. Kreutz-Delgado). Proceedings of the First IAPR Workshop on Cognitive Information Processing (CIP 2008), pp. 126-131, June 2008.
A Unifying Viewpoint of some Clustering Techniques Using Bregman Divergences and Extensions to Mixed Data Sets (with B. Burdge, K. Kreutz-Delgado and U. F. Mayer). Proceedings of the First IEEE International Workshop on Data Mining and Artificial Intelligence (DMAI 2008) held in conjunction with the Eleventh IEEE International Conference on Computer and Information Technology, pp. 56-63, Dec. 2008.
Classifying Non-Gaussian and Mixed Data Sets in Their Natural Parameter Space (with U. F. Mayer and K. Kreutz-Delgado). Accepted for Publication in the Proceedings of the Nineteenth IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2009), Sept. 2009.
Generalized Statistical Methods for Mixed Exponential Families, Part I: Theoretical Foundations (with K. Kreutz-Delgado and U. F. Mayer). Submitted for Publication to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Sept. 2009.
Generalized Statistical Methods for Mixed Exponential Families, Part II: Applications (with U. F. Mayer and K. Kreutz-Delgado). Submitted for Publication to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Sept. 2009.

Last updated: Tue Sep 22 11:35:37 PST 2009