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We obtain a critical imbedding and then, concentration-compactness principles for fractional Sobolev spaces with variable exponents. As an application of these results, we obtain the existence of many solutions for a class of critical…

Analysis of PDEs · Mathematics 2019-09-23 Ky Ho , Yun-Ho Kim

We investigate the asymptotic behavior of probability measures associated with stochastic dynamical systems featuring either globally contracting or $B_{r}$-contracting drift terms. While classical results often assume constant diffusion…

Dynamical Systems · Mathematics 2025-05-14 Simone Betteti , Francesco Bullo

This work concerns random dynamics of hyperbolic entire and meromorphic functions of finite order and whose derivative satisfies some growth condition at infinity. This class contains most of the classical families of transcendental…

Dynamical Systems · Mathematics 2017-02-06 Volker Mayer , Mariusz Urbanski

Exhibiting a new type of measure concentration, we prove uniform concentration bounds for measurable Lipschitz functions on product spaces, where Lipschitz is taken with respect to the metric induced by a weighted covering of the index set…

Probability · Mathematics 2020-12-23 Friedrich Martin Schneider , Sławomir Solecki

We prove well-posedness and higher-order regularity for a linear structurally damped plate equation with inhomogeneous Dirichlet--Neumann boundary conditions on the half-space and on bounded domains. To this end, we study maximal regularity…

Analysis of PDEs · Mathematics 2026-03-02 Robert Denk , Floris Roodenburg

We obtain the first results on convergence rates in the Prokhorov metric for the weak invariance principle (functional central limit theorem) for deterministic dynamical systems. Our results hold for uniformly expanding/hyperbolic (Axiom A)…

Dynamical Systems · Mathematics 2021-07-28 Marios Antoniou , Ian Melbourne

Ising models describe the joint probability distribution of a vector of binary feature variables. Typically, not all the variables interact with each other and one is interested in learning the presumably sparse network structure of the…

Machine Learning · Computer Science 2019-07-09 Frank Nussbaum , Joachim Giesen

We study the ferromagnetic random field Ising model (RFIM) on a graph $G=(V,E)$ having maximal degree $\Delta$, where the external field at each vertex is an i.i.d. random variable. When the random field distribution is sufficiently…

Probability · Mathematics 2026-05-05 Yi Han

We study the question of whether submodular functions of random variables satisfying various notions of negative dependence satisfy Chernoff-like concentration inequalities. We prove such a concentration inequality for the lower tail when…

Data Structures and Algorithms · Computer Science 2024-09-27 Sharmila Duppala , George Z. Li , Juan Luque , Aravind Srinivasan , Renata Valieva

We consider the minimization of submodular functions subject to ordering constraints. We show that this optimization problem can be cast as a convex optimization problem on a space of uni-dimensional measures, with ordering constraints…

Machine Learning · Computer Science 2017-07-31 Francis Bach

This paper conducts sensitivity analysis of random constraint and variational systems related to stochastic optimization and variational inequalities. We establish efficient conditions for well-posedness, in the sense of robust Lipschitzian…

Optimization and Control · Mathematics 2021-12-13 Boris S. Mordukhovich , Pedro Pérez-Aros

We consider graphical models based on a recursive system of linear structural equations. This implies that there is an ordering, $\sigma$, of the variables such that each observed variable $Y_v$ is a linear function of a variable specific…

Methodology · Statistics 2019-06-28 Y. Samuel Wang , Mathias Drton

In a recent paper [P. Mayer et al., Phys. Rev. Lett. 93, 115701 (2004)] it was shown, by means of experiments, theory and simulations, that coarsening systems display dynamic heterogeneity analogous to that of glass formers. Here, we…

Statistical Mechanics · Physics 2007-05-23 Peter Mayer , Peter Sollich , Ludovic Berthier , Juan P. Garrahan

This study deals with continuous limits of interacting one-dimensional diffusive systems, arising from stochastic distortions of discrete curves with various kinds of coding representations. These systems are essentially of a…

Statistical Mechanics · Physics 2011-09-09 Guy Fayolle , Cyril Furtlehner

We give a concentration inequality based on the premise that random variables take values within a particular region. The concentration inequality guarantees that, for any sequence of correlated random variables, the difference between the…

Probability · Mathematics 2020-02-21 Go Kato

Mixtures are convex combinations of laws. Despite this simple definition, a mixture can be far more subtle than its mixed components. For instance, mixing Gaussian laws may produce a potential with multiple deep wells. We study in the…

Probability · Mathematics 2010-06-16 Djalil Chafai , Florent Malrieu

The Wolff dynamics is a non-local Markov chain widely used for simulating the Ising model due to its effectiveness in reducing critical slowing down compared to the Glauber dynamics. Despite extensive algorithmic and numerical studies, a…

Probability · Mathematics 2026-05-29 Kaiyuan Cui , Fuzhou Gong

We consider higher order viscous Burgers' equations with generalized nonlinearity and study the associated initial value problems for given data in the $L^2$-based Sobolev spaces. We introduce appropriate time weighted spaces to derive…

Analysis of PDEs · Mathematics 2015-06-02 Xavier Carvajal , Mahendra Panthee

We obtain a Bernstein type Gaussian concentration inequality for martingales. Our inequality improves the Azuma-Hoeffding inequality for moderate deviations $x$. Following the work of McDiarmid (1989), Talagrand (1996) and Boucheron, Lugosi…

Probability · Mathematics 2017-10-17 Xiequan Fan

The pairwise influence matrix of Dobrushin has long been used as an analytical tool to bound the rate of convergence of Gibbs sampling. In this work, we use Dobrushin influence as the basis of a practical tool to certify and efficiently…

Machine Learning · Statistics 2017-07-20 Ioannis Mitliagkas , Lester Mackey
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