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Sébastien Bubeck

59 papers hereh-index 4712.5k citations94 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author39
  • middle author13
  • last author5

Across the 58 of 59 papers where every author was matched, so the position is known.

fields
  • cs.LG16
  • cs.DS10
  • math.OC10
  • stat.ML8
  • math.PR6
  • math.ST3
same name
  • Sébastien Bubeck — 30 papers, h 20
  • Sébastien Bubeck — 5 papers, h 5
  • Sébastien Bubeck — 3 papers
  • Sébastien Bubeck — 2 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
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

collaborators
Showing 2016Show all

4 papers · 1 filter

cs.DS2016

Local max-cut in smoothed polynomial time

Omer Angel, Sébastien Bubeck, Yuval Peres +1

In 1988, Johnson, Papadimitriou and Yannakakis wrote that "Practically all the empirical evidence would lead us to conclude that finding locally optimal solutions is much easier th…

math.ST2016

Basic models and questions in statistical network analysis

Miklos Z. Racz, Sébastien Bubeck

Extracting information from large graphs has become an important statistical problem since network data is now common in various fields. In this minicourse we will investigate the…

cs.LG2016

Kernel-based methods for bandit convex optimization

Sébastien Bubeck, Ronen Eldan, Yin Tat Lee

We consider the adversarial convex bandit problem and we build the first poly(T)-time algorithm with poly(n)T​-regret for this problem. To do so we int…

math.OC2016★ 2 cited

Black-box optimization with a politician

Sébastien Bubeck, Yin-Tat Lee

We propose a new framework for black-box convex optimization which is well-suited for situations where gradient computations are expensive. We derive a new method for this framewor…

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