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We study sampling problems associated with non-convex potentials that meanwhile lack smoothness. In particular, we consider target distributions that satisfy either logarithmic-Sobolev inequality or Poincar\'e inequality. Rather than…

Machine Learning · Computer Science 2023-02-21 Jiaming Liang , Yongxin Chen

Threshold phenomena are investigated using a general approach, following Talagrand [Ann. Probab. 22 (1994) 1576--1587] and Friedgut and Kalai [Proc. Amer. Math. Soc. 12 (1999) 1017--1054]. The general upper bound for the threshold width of…

Probability · Mathematics 2016-08-16 Raphaël Rossignol

We show sharpened forms of the concentration of measure phenomenon typically centered at stochastic expansions of order $d-1$ for any $d \in \mathbb{N}$. Here we focus on differentiable functions on the Euclidean space in presence of a…

Probability · Mathematics 2019-11-26 Friedrich Götze , Holger Sambale

We consider a random variable $X$ that takes values in a (possibly infinite-dimensional) topological vector space $\mathcal{X}$. We show that, with respect to an appropriate "normal distance" on $\mathcal{X}$, concentration inequalities for…

Probability · Mathematics 2010-09-27 Timothy John Sullivan , Houman Owhadi

Let $X$ be a random variable and define its concentration function by $$\mathcal{Q}_{h}(X)=\sup_{x\in \mathbb{R}}\mathbb{P}(X\in (x,x+h]).$$ For a sum $S_n=X_1+\cdots+X_n$ of independent real-valued random variables the Kolmogorov-Rogozin…

Probability · Mathematics 2022-01-25 Tomas Juškevičius

We introduce a framework for obtaining tight mixing times for Markov chains based on what we call restricted modified log-Sobolev inequalities. Modified log-Sobolev inequalities (MLSI) quantify the rate of relative entropy contraction for…

Data Structures and Algorithms · Computer Science 2021-11-08 Nima Anari , Vishesh Jain , Frederic Koehler , Huy Tuan Pham , Thuy-Duong Vuong

Many psychological theories can be operationalized as linear inequality constraints on the parameters of multinomial distributions (e.g., discrete choice analysis). These constraints can be described in two equivalent ways: Either as the…

Computation · Statistics 2019-04-23 Daniel W. Heck , Clintin P. Davis-Stober

The exponential ergodicity of partially dissipative McKean-Vlasov SDEs in the \(L^1\)-Wasserstein distance has been extensively studied using asymptotic reflection coupling. However, the reflection coupling method is not applicable for the…

Probability · Mathematics 2025-11-13 Xing Huang , Eva Kopfer , Panpan Ren

For the task of sampling from a density $\pi \propto \exp(-V)$ on $\mathbb{R}^d$, where $V$ is possibly non-convex but $L$-gradient Lipschitz, we prove that averaged Langevin Monte Carlo outputs a sample with $\varepsilon$-relative Fisher…

Statistics Theory · Mathematics 2022-02-11 Krishnakumar Balasubramanian , Sinho Chewi , Murat A. Erdogdu , Adil Salim , Matthew Zhang

Threshold-type counts based on multivariate occupancy models with log concave marginals admit bounded size biased couplings under weak conditions, leading to new concentration of measure results for random graphs, germ-grain models in…

Probability · Mathematics 2017-05-25 Jay Bartroff , Larry Goldstein , Ümit Işlak

Concentration of measure has been argued to be the fundamental cause of adversarial vulnerability. Mahloujifar et al. presented an empirical way to measure the concentration of a data distribution using samples, and employed it to find…

Machine Learning · Computer Science 2021-03-25 Jack Prescott , Xiao Zhang , David Evans

Common proofs of the Gagliardo-Nirenberg-Sobolev (GNS) do not provide explicit bounds on the involved constants, unless a sharp constant is being determined. GNS inequalities naturally occur in error estimates for numerical approximations.…

Functional Analysis · Mathematics 2024-08-06 Michael Hott

This paper gives a review of concentration inequalities which are widely employed in non-asymptotical analyses of mathematical statistics in a wide range of settings, from distribution-free to distribution-dependent, from sub-Gaussian to…

Statistics Theory · Mathematics 2025-02-24 Huiming Zhang , Song Xi Chen

In this note we bound the deficit in the logarithmic Sobolev Inequality and in the Talagrand transport-entropy Inequality for the Gaussian measure, in any dimension, by mean of a distance introduced by Bucur and Fragal\`a.

Functional Analysis · Mathematics 2015-07-01 Filomena Feo , Maria Rosaria Posteraro , Cyril Roberto

We use here a particle system to prove a convergence result as well as a deviation inequality for solutions of granular media equation when the confinement potential and the interaction potential are no more uniformly convex. Proof is…

Probability · Mathematics 2007-05-23 Patrick Cattiaux , Guillin Arnaud , Malrieu Florent

We continue the study of convergence of multipole pluricomplex Green functions for a bounded hyperconvex domain of $\mathbb C^n$, in the case where poles collide. We consider the case where all poles do not converge to the same point in the…

Complex Variables · Mathematics 2017-10-24 Nguyen Quand Dieu , Pascal J. Thomas

Using Talagrand's concentration inequality on the discrete cube {0,1}^m we show that given a real-valued function Z(x)on {0,1}^m that satisfies certain monotonicity conditions one can control the deviations of Z(x) above its median by a…

Probability · Mathematics 2007-05-23 Dmitry Panchenko

We revisit entropy methods to prove new sharp trace logarithmic Sobolev and sharp Gagliardo-Nirenberg-Sobolev inequalities on the half space, with a focus on the entropy inequality itself and not the actual flow, allowing for somewhat…

Analysis of PDEs · Mathematics 2021-12-28 Simon Zugmeyer

In this paper, we develop a simulation-based approach to optimisation with multi-modal functions using slice sampling. Our method specifies the objective function as an energy potential in a Boltzmann distribution and then we use auxiliary…

Optimization and Control · Mathematics 2012-12-11 John R. Birge , Nicholas G. Polson

We prove Wasserstein contraction of simple slice sampling for approximate sampling w.r.t. distributions with log-concave and rotational invariant Lebesgue densities. This yields, in particular, an explicit quantitative lower bound of the…

Probability · Mathematics 2020-09-17 Viacheslav Natarovskii , Daniel Rudolf , Björn Sprungk
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