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             Department of Systems Engineering and Engineering Management

                     The Chinese University of Hong Kong

 

 

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Date: Friday, November 20, 2020, 16:30 to 17:30

 

Title: ROBUST SUBGAUSSIAN ESTIMATION OF A MEAN VECTOR IN NEARLY LINEAR TIME  

 

Speaker: Prof. Guillaume Lecué

 

Abstract:

 

Robust mean estimation has witnessed an increasing interest the last ten years in both statistics and computer sciences. We will first review the literature in this domain. Then, we will present the construction of an algorithm, running in nearly linear time. The algorithm is fully data-dependent and does not use in its construction the proportion of outliers nor the rate above. Its construction combines recently developed tools for Median-of-Means estimators and covering-Semi-definite Programming. We also show how this algorithm can automatically adapt to the number of outliers. 

 

Biography:

 

Guillaume Lecué graduated from Ecole Normale Supérieure deCachan, France, and received the M.Sc. degree in applied mathematics from Université Paris XI - Orsay, France, in 2005. He received the Ph.D. degree in statistics at Université Paris VI - Jussieu, France,in 2007, where Prof. A. Tsybakov served as his advisor. He completed his habilitation degree in 2008 at the Laboratoire d’analyseet mathématiques appliquées, Université Paris-Est Marne-la-vallée,France. He is currently Professor at CREST-ENSAE. His research interests are in the areas of learning theory, empirical process theory, high-dimensional phenomenons and robustness. Dr. Lecué received the "Mark Fulk award" for the best student paper at the 2006 Conference on Learning Theory COLT06, Pittsburgh,PA and the "Prix de la chancellerie des Universités de Paris" for the best Ph.D. thesis in mathematics and its applications defended in Paris in 2007.