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Concentration and compression over infinite alphabets, mixing times of random walks on random graphs

Abstract : This document presents the problems I have been interested in during my PhD thesis. I begin with a concise presentation of the main results, followed by three relatively independent parts. In the first part, I consider statistical inference problems on an i.i.d. sample from an unknown distribution over a countable alphabet. The first chapter is devoted to the concentration properties of the sample's profile and of the missing mass. This is a joint work with Stéphane Boucheron and Mesrob Ohannessian. After obtaining bounds on variances, we establish Bernstein-type concentration inequalities and exhibit a vast domain of sampling distributions for which the variance factor in these inequalities is tight. The second chapter presents a work in progress with Stéphane Boucheron and Elisabeth Gassiat, on the problem of universal adaptive compression over countable alphabets. We give bounds on the minimax redundancy of envelope classes, and construct a quasi-adaptive code on the collection of classes defined by a regularly varying envelope. In the second part, I consider random walks on random graphs with prescribed degrees. I first present a result obtained with Justin Salez, establishing the cutoff phenomenon for non-backtracking random walks. Under certain degree assumptions, we precisely determine the mixing time, the cutoff window, and show that the profile of the distance to equilibrium converges to the Gaussian tail function. Then I consider the problem of comparing the mixing times of the simple and non-backtracking random walks. The third part is devoted to the concentration properties of weighted sampling without replacement and corresponds to a joint work with Yuval Peres and Justin Salez.
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Submitted on : Thursday, March 15, 2018 - 12:07:13 PM
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Anna Ben-Hamou. Concentration and compression over infinite alphabets, mixing times of random walks on random graphs. General Mathematics [math.GM]. Université Sorbonne Paris Cité, 2016. English. ⟨NNT : 2016USPCC197⟩. ⟨tel-01376929v2⟩



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