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Menon's proof of the preservation of log-concavity of sequences under convolution becomes simpler when adapted to 2-sided infinite sequences. Under assumption of log-concavity of two 2-sided infinite sequences, the existence of the…

Combinatorics · Mathematics 2019-03-07 Stephan Foldes , Laszlo Major

We prove the following type of discrete entropy monotonicity for sums of isotropic, log-concave, independent and identically distributed random vectors $X_1,\dots,X_{n+1}$ on $\mathbb{Z}^d$: $$ H(X_1+\cdots+X_{n+1}) \geq H(X_1+\cdots+X_{n})…

Probability · Mathematics 2025-12-18 Matthieu Fradelizi , Lampros Gavalakis , Martin Rapaport

We investigate concentration inequalities for Dirichlet and Multinomial random variables.

Machine Learning · Computer Science 2020-02-03 Jian Qian , Ronan Fruit , Matteo Pirotta , Alessandro Lazaric

We give concentration bounds for martingales that are uniform over finite times and extend classical Hoeffding and Bernstein inequalities. We also demonstrate our concentration bounds to be optimal with a matching anti-concentration…

Probability · Mathematics 2015-12-03 Akshay Balsubramani

In this note we derive a sharp concentration inequality for the supremum of a smooth random field over a finite dimensional set. It is shown that this supremum can be bounded with high probability by the value of the field at some…

Statistics Theory · Mathematics 2013-07-08 Denis Belomestny , Vladimir Spokoiny

Given a suitably normalized $X\in\mathbb{R}^n$ we observe that the function $\theta\mapsto\mathbb{E}|X\cdot\theta|$, defined for $\theta\in S^{n-1}$, admits surprisingly strong concentration far surpassing what is expected on account of…

Functional Analysis · Mathematics 2020-08-04 Erez Buchweitz

This paper deduces exponential matrix concentration from a Poincar\'e inequality via a short, conceptual argument. Among other examples, this theory applies to matrix-valued functions of a uniformly log-concave random vector. The proof…

Probability · Mathematics 2021-01-08 De Huang , Joel A. Tropp

We explore the applications of our previously established likelihood-ratio method for deriving concentration inequalities for a wide variety of univariate and multivariate distributions. New concentration inequalities for various…

Statistics Theory · Mathematics 2014-09-23 Xinjia Chen

We derive concentration inequalities for functions of the empirical measure of large random matrices with infinitely divisible entries and, in particular, stable ones. We also give concentration results for some other functionals of these…

Probability · Mathematics 2007-06-13 Christian Houdré , Hua Xu

By the Pr\'ekopa-Leindler inequality, the difference $X-X'$ has a log-concave density provided that $X$ has a log-concave density and $X, X'$ are independent and identically distributed. We prove that the opposite direction does not always…

Probability · Mathematics 2025-12-30 Min Wang

This work studies the location estimation problem for a mixture of two rotation invariant log-concave densities. We demonstrate that Least Squares EM, a variant of the EM algorithm, converges to the true location parameter from a randomly…

Machine Learning · Statistics 2019-06-21 Wei Qian , Yuqian Zhang , Yudong Chen

We derive novel anti-concentration bounds for the difference between the maximal values of two Gaussian random vectors across various settings. Our bounds are dimension-free, scaling with the dimension of the Gaussian vectors only through…

Statistics Theory · Mathematics 2024-08-27 Alexandre Belloni , Ethan X. Fang , Shuting Shen

We consider variational problems that model the bending behavior of curves that are constrained to belong to given hypersurfaces. Finite element discretizations of corresponding functionals are justified rigorously via Gamma-convergence.…

Numerical Analysis · Mathematics 2020-04-24 Sören Bartels

We provide a mild sufficient condition for a probability measure on the real line to satisfy a modified log-Sobolev inequality for convex functions, interpolating between the classical log-Sobolev inequality and a Bobkov-Ledoux type…

Probability · Mathematics 2016-08-08 Radosław Adamczak , Michał Strzelecki

We establish a new comparison between the Legendre transform of the cumulant generating function and the half-space depth of an arbitrary log-concave probability distribution on the real line, that carries on to the multidimensional…

Probability · Mathematics 2025-06-17 Silouanos Brazitikos , Giorgos Chasapis

For an unknown continuous distribution on a real line, we consider the approximate estimation by the discretization. There are two methods for the discretization. First method is to divide the real line into several intervals before taking…

Statistics Theory · Mathematics 2017-10-12 Yo Sheena

We study the problem of sampling from strongly log-concave distributions over $\mathbb{R}^d$ using the Poisson midpoint discretization (a variant of the randomized midpoint method) for overdamped/underdamped Langevin dynamics. We prove its…

Probability · Mathematics 2025-10-02 Rishikesh Srinivasan , Dheeraj Nagaraj

We establish upper bounds for tails of order statistics of isotropic log-concave vectors and apply them to derive a concentration of l_r norms of such vectors.

Probability · Mathematics 2014-09-19 Rafał Latała

We prove log-concavity of exit probabilities of lattice random walks in certain planar regions.

Combinatorics · Mathematics 2023-05-11 Swee Hong Chan , Igor Pak , Greta Panova

We examine the concentration of uniform generalization errors around their expectation in binary linear classification problems via an isoperimetric argument. In particular, we establish Poincar\'{e} and log-Sobolev inequalities for the…

Machine Learning · Statistics 2025-06-27 Shogo Nakakita