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Title: On high-dimensional robust regression and inefficiency of maximum likelihood methods Abstract: I will discuss the behavior of widely used statistical methods in the high-dimensional setting where the number of observations, n, and the number of predictors, p, are both large. I will present limit theorems about the behavior of the corresponding estimators, their asymptotic risks etc... The results apply not only to robust regression estimators, but also Lasso-type estimators and many much more complicated problems. Some of the results answer a question raised by Huber in his seminal '73... Read more about CMSA Talk: Noureddine El Karoui

A Conversation with Bob O'Neill Registration required for presentation (free)