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University of Cambridge > Talks.cam > Probability > Talagrand's concentration inequality for empirical processes
Talagrand's concentration inequality for empirical processesAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Berestycki. This is an expository talk about a deep probability inequality due to Talagrand (Invent. Math. 1996, cf. Ledoux’s book in 2001), which gives a Prohorov- (and then also Bernstein-) type exponential bound for the concentration of the supremum of an empirical process around its mean. I will try to discuss the following points: A) Some ideas of the proof, in particular the proof due to Ledoux using logarithmic Sobolev inequalities, which is related to the more general “concentration of measure” phenomenon. B) Discuss a variety of probabilistic applications, which should show how versatile this inequality is, in particular that it reproduces most known exp. inequalities for i.i.d. sums of (possibly Banach-)valued random variables. C) Discuss recent statistical applications to adaptive estimation, model selection problems, Rademacher processes, and almost sure limit laws (LIL-type results). This talk is part of the Probability series. This talk is included in these lists:
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