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20092023
most citedProvably Robust Deep Learning via Adversarially Trained Smoothed Classifiers

261 citations · 1.4k across the 45 of their papers we have counts for

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Showing 2014Show all

7 papers · 1 filter

math.OC2014★ 21 cited

The entropic barrier: a simple and optimal universal self-concordant barrier

Sébastien Bubeck, Ronen Eldan

We prove that the Cramér transform of the uniform measure on a convex body in is a -self-concordant barrier, improving a seminal result of Nesterov and N…

math.ST2014

Testing for high-dimensional geometry in random graphs

Sébastien Bubeck, Jian Ding, Ronen Eldan +1

We study the problem of detecting the presence of an underlying high-dimensional geometric structure in a random graph. Under the null hypothesis, the observed graph is a realizati…

math.PR2014

Finding Adam in random growing trees

Sébastien Bubeck, Luc Devroye, Gábor Lugosi

We investigate algorithms to find the first vertex in large trees generated by either the uniform attachment or preferential attachment model. We require the algorithm to output a…

math.PR2014

From trees to seeds: on the inference of the seed from large trees in the uniform attachment model

Sébastien Bubeck, Ronen Eldan, Elchanan Mossel +1

We study the influence of the seed in random trees grown according to the uniform attachment model, also known as uniform random recursive trees. We show that different seeds lead…

math.OC2014

Convex Optimization: Algorithms and Complexity

Sébastien Bubeck

This monograph presents the main complexity theorems in convex optimization and their corresponding algorithms. Starting from the fundamental theory of black-box optimization, the…

stat.ML2014★ 3 cited

Most Correlated Arms Identification

Che-Yu Liu, Sébastien Bubeck

We study the problem of finding the most mutually correlated arms among many arms. We show that adaptive arms sampling strategies can have significant advantages over the non-adapt…