We prove that given a nearly log-concave density, in any partition of the space to two well separated sets, the measure of the points that do not belong to these sets is large. We apply this isoperimetric inequality to derive lower bounds on the generalization error in learning. We also show that when..
AbstractA weak version of a conjecture stated by Kannan, Lovász and Simonovits claims that an isotro...
We present theoretical properties of the log-concave maximum likelihood estimator of a density based...
Given a probability measure $\mu $ on ${\mathbb R}^n$, Tukey's half-space depth is defined for any $...
Abstract — We prove that given a nearly log-concave distribu-tion, in any partition of the space to ...
in Lectures Notes in Mathematics, n°2116Chaining techniques show that if X is an isotropic log-conca...
The purpose of this paper is to analyze the isoperimetric inequality for symmetric log-convex probab...
Abstract. Given an isotropic random vector X with log-concave density in Eu-clidean space Rn, we stu...
We provide new results concerning label efficient, polynomial time, passive and active learning of l...
Abstract. The purpose of this paper is to analyze the isoperimetric inequality for sym-metric log-co...
We study the adaptation properties of the multivariate log-concave maximum likelihood estimator over...
Abstract. Efficient sampling, integration and optimization algorithms for logconcave functions [BV04...
International audienceThe goal of this paper is to push forward the study of those properties of log...
The log-concave maximum likelihood estimator of a density on the real line based on a sample of size...
International audienceAn elementary proof is provided of sharp bounds for the varentropy of random v...
AbstractIn this article, we generalize a localization theorem of Lovász and Simonovits [Random walks...
AbstractA weak version of a conjecture stated by Kannan, Lovász and Simonovits claims that an isotro...
We present theoretical properties of the log-concave maximum likelihood estimator of a density based...
Given a probability measure $\mu $ on ${\mathbb R}^n$, Tukey's half-space depth is defined for any $...
Abstract — We prove that given a nearly log-concave distribu-tion, in any partition of the space to ...
in Lectures Notes in Mathematics, n°2116Chaining techniques show that if X is an isotropic log-conca...
The purpose of this paper is to analyze the isoperimetric inequality for symmetric log-convex probab...
Abstract. Given an isotropic random vector X with log-concave density in Eu-clidean space Rn, we stu...
We provide new results concerning label efficient, polynomial time, passive and active learning of l...
Abstract. The purpose of this paper is to analyze the isoperimetric inequality for sym-metric log-co...
We study the adaptation properties of the multivariate log-concave maximum likelihood estimator over...
Abstract. Efficient sampling, integration and optimization algorithms for logconcave functions [BV04...
International audienceThe goal of this paper is to push forward the study of those properties of log...
The log-concave maximum likelihood estimator of a density on the real line based on a sample of size...
International audienceAn elementary proof is provided of sharp bounds for the varentropy of random v...
AbstractIn this article, we generalize a localization theorem of Lovász and Simonovits [Random walks...
AbstractA weak version of a conjecture stated by Kannan, Lovász and Simonovits claims that an isotro...
We present theoretical properties of the log-concave maximum likelihood estimator of a density based...
Given a probability measure $\mu $ on ${\mathbb R}^n$, Tukey's half-space depth is defined for any $...
DOI
Add to ORKG