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Aurélie Lozano received the M.S./Dipl.Ing. degree in Communication Systems from the Swiss Federal Institute of Technology Lausanne (EPFL) in 2001, and the M.A. and Ph.D. degrees in Electrical Engineering from Princeton University respectively in 2004 and 2007. Her Ph.D. thesis, "Asymptotics of Boosting, Greedy Learning Algorithms, and Wireless Networks”, studies the convergence and consistency of Boosting and related machine learning algorithms, and the throughput capacity of wireless ad-hoc networks with restricted mobility.
Aurélie joined the Data Analytics Research Group as a Research Staff Member in July 2007. Her research interests are in Machine Learning, Data Mining, and their applications to problems in business analytics.
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ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)pp.1-5, (2023)
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arXiv: Learning (2019)
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international conference on machine learningpp.7242-7251, (2019)
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