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We study estimation of multivariate densities $p$ of the form $p(x)=h(g(x))$ for $x\in \mathbb {R}^d$ and for a fixed monotone function $h$ and an unknown convex function $g$. The canonical example is $h(y)=e^{-y}$ for $y\in \mathbb {R}$;…

Statistics Theory · Mathematics 2012-11-15 Arseni Seregin , Jon A. Wellner

We consider stochastic differential equations on $\mathbb R^d$ with coefficients depending on the path and distribution for the whole history. Under a local integrability condition on the time-spatial singular drift, the well-posedness and…

Probability · Mathematics 2025-07-15 Feng-Yu Wang , Chenggui Yuan , Xiao-Yu Zhao

An inequality of Brascamp and Lieb provides a bound on the covariance of two functions with respect to log-concave measures. The bound estimates the covariance by the product of the $L^2$ norms of the gradients of the functions, where the…

Functional Analysis · Mathematics 2011-10-25 Eric A. Carlen , Dario Cordero-Erausquin , Elliott H. Lieb

Probability distributions defined on the half space are known to be quite different from those in the full space. Here, a nonextensive entropic treatment is presented for the half space in an analytic and self-consistent way. In this…

Statistical Mechanics · Physics 2007-05-23 A. K. Rajagopal , Sumiyoshi Abe

We establish sharp exponential deviation estimates of the information content as well as a sharp bound on the varentropy for the class of convex measures on Euclidean spaces. This generalizes a similar development for log-concave measures…

Probability · Mathematics 2020-02-25 Matthieu Fradelizi , Jiange Li , Mokshay Madiman

We propose an inequality between the longitudinally polarized density and the transversity of a quark in a nucleon. This inequality, whose validity is limited to very small scales, is based on considerations about Lorentz transformations…

High Energy Physics - Phenomenology · Physics 2007-05-23 Elvio Di Salvo

We prove that the Poisson distribution maximises entropy in the class of ultra-log-concave distributions, extending a result of Harremo\"{e}s. The proof uses ideas concerning log-concavity, and a semigroup action involving adding Poisson…

Probability · Mathematics 2010-08-17 Oliver Johnson

By differentiating a concavity principle arising from the Pr\'ekopa-Leindler inequality, we obtain a statement simultaneously strengthening the weighted boundary Poincar\'e inequality and the Brascamp-Lieb variance inequality. The resulting…

Functional Analysis · Mathematics 2026-02-27 Sotiris Armeniakos , Jacopo Ulivelli

We study specific properties of particles transport by exploring an exact solvable model, a so-called comb structure, where diffusive transport of particles leads to subdiffusion. A performance of L\'evy -- like process enriches this…

Disordered Systems and Neural Networks · Physics 2007-05-23 E. Baskin , A. Iomin

We compare weighted sums of i.i.d. positive random variables according to the usual stochastic order. The main inequalities are derived using majorization techniques under certain log-concavity assumptions. Specifically, let $Y_i$ be i.i.d.…

Probability · Mathematics 2011-07-19 Yaming Yu

Let X be a normal variety such that $K_X$ is Q-Cartier, and let $f: X \rightarrow X$ be a finite surjective morphism of degree at least two. We establish a close relation between the irreducible components of the locus of singularities that…

Algebraic Geometry · Mathematics 2017-10-30 Amaël Broustet , Andreas Höring

We introduce two probabilistic models of random log-concave polynomials, the uniform model and the beta model, and study the asymptotic distribution of their zeros in the complex plane. In the uniform model, we show that the empirical root…

Probability · Mathematics 2026-04-10 Ohad Noy Feldheim , Arnab Sen

We establish a log-Sobolev inequality for the stationary distribution of mean-field Langevin dynamics with a constant that is independent of the number of particles $N$. Our proof proceeds by establishing the existence of a Lipschitz…

Probability · Mathematics 2024-09-17 Sinho Chewi , Atsushi Nitanda , Matthew S. Zhang

We provide a counterexample to a conjecture by B. Connelly about density of circle packings

Metric Geometry · Mathematics 2021-04-28 Thomas Fernique , Daria Pchelina

We study the problem of estimating multivariate log-concave probability density functions. We prove the first sample complexity upper bound for learning log-concave densities on $\mathbb{R}^d$, for all $d \geq 1$. Prior to our work, no…

Machine Learning · Computer Science 2017-06-07 Ilias Diakonikolas , Daniel M. Kane , Alistair Stewart

Let $p$ be a polynomial in the non-commuting variables $(a,x)=(a_1,...,a_{g_a},x_1,...,x_{g_x})$. If $p$ is convex in the variables $x$, then $p$ has degree two in $x$ and moreover, $p$ has the form $p = L + \Lambda ^T \Lambda,$ where $L$…

Functional Analysis · Mathematics 2008-04-07 Damon M. Hay , J. William Helton , Adrian Lim , Scott McCullough

Let $e_{n}^k$ be the entries in the classical Euler's difference table. We consider the array $d_{n}^{k}=e_n^k/k!$ for $0\leq k \leq n$, where $d_n^k$ can be interpreted as the number of k-fixed-points-permutations of [n]. We show that the…

Combinatorics · Mathematics 2009-11-17 William Y. C. Chen , Cindy C. Y. Gu , Kevin J. Ma , Larry X. W. Wang

A weighted relative isoperimetric inequality in convex cones is obtained via the Monge-Ampere equation. The method improves several inequalities in the literature, e.g. constants in a theorem of Cabre--Ros--Oton--Serra. Applications are…

Analysis of PDEs · Mathematics 2021-12-14 Emanuel Indrei

We study the expected volume of random polytopes generated by taking the convex hull of independent identically distributed points from a given distribution. We show that for log-concave distributions supported on convex bodies, we need at…

Metric Geometry · Mathematics 2021-11-16 Debsoumya Chakraborti , Tomasz Tkocz , Beatrice-Helen Vritsiou

A key task in Bayesian statistics is sampling from distributions that are only specified up to a partition function (i.e., constant of proportionality). However, without any assumptions, sampling (even approximately) can be #P-hard, and few…

Machine Learning · Computer Science 2018-12-03 Rong Ge , Holden Lee , Andrej Risteski