output
20102023
most citedTensorizing Neural Networks

604 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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7 papers · 1 filter

math.ST2019★ 6 cited

Affine Invariant Covariance Estimation for Heavy-Tailed Distributions

Dmitrii Ostrovskii, Alessandro Rudi

In this work we provide an estimator for the covariance matrix of a heavy-tailed multivariate distributionWe prove that the proposed estimator admits an \tex…

math.ST2018★ 127 cited

Sample Complexity of Sinkhorn divergences

Aude Genevay, Lénaic Chizat, Francis Bach +2

Optimal transport (OT) and maximum mean discrepancies (MMD) are now routinely used in machine learning to compare probability measures. We focus in this paper on \emph{Sinkhorn div…

math.ST2015★ 139 cited

Batched bandit problems

Vianney Perchet, Philippe Rigollet, Sylvain Chassang +1

Motivated by practical applications, chiefly clinical trials, we study the regret achievable for stochastic bandits under the constraint that the employed policy must split trials…

math.ST2013★ 39 cited

Adaptivity of averaged stochastic gradient descent to local strong convexity for logistic regression

Francis Bach

In this paper, we consider supervised learning problems such as logistic regression and study the stochastic gradient method with averaging, in the usual stochastic approximation s…

math.ST2012★ 54 cited

Choice of V for V-Fold Cross-Validation in Least-Squares Density Estimation

Sylvain Arlot, Matthieu Lerasle

This paper studies V-fold cross-validation for model selection in least-squares density estimation. The goal is to provide theoretical grounds for choosing V in order to minimize t…

math.ST2011★ 48 cited

Multi-task Regression using Minimal Penalties

Matthieu Solnon, Sylvain Arlot, Francis Bach

In this paper we study the kernel multiple ridge regression framework, which we refer to as multi-task regression, using penalization techniques. The theoretical analysis of this p…

math.ST2010★ 10 cited

Linear regression through PAC-Bayesian truncation

Jean-Yves Audibert, Olivier Catoni

We consider the problem of predicting as well as the best linear combination of d given functions in least squares regression under L^\infty constraints on the linear combination.…