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In this paper we show that the realization in $L^p(X,\nu_\infty)$ of the nonsymmetric Ornstein-Uhlenbeck operator $L$ is sectorial for any $p\in(1,+\infty)$ and we provide an explicit sector of analyticity. Here $(X,\mu_\infty,H_\infty)$ is…

Functional Analysis · Mathematics 2019-12-06 Davide Addona

The asymptotic behaviour of empirical measures has plenty of studies. However, the research on conditional empirical measures is limited. Being the development of Wang \cite{eW1}, under the quadratic Wasserstein distance, we investigate the…

Probability · Mathematics 2022-04-29 Huaiqian Li , Bingyao Wu

We continue our study of the dynamics of mappings with small topological degree on (projective) complex surfaces. Previously, under mild hypotheses, we have constructed an ergodic ``equilibrium'' measure for each such mapping. Here we study…

Dynamical Systems · Mathematics 2009-09-10 Jeffrey Diller , Romain Dujardin , Vincent Guedj

In this paper, we obtain some exact $L_2$ Bernstein-Markov inequalities for generalized Hermite and Gegenbauer weight. More precisely, we determine the exact values of the extremal problem $$M_n^2(L_2(W_\lambda),{\rm D}):=\sup_{0\neq…

Classical Analysis and ODEs · Mathematics 2024-11-26 Jiansong Li , Jiaxin Geng , Yun Ling , Heping Wang

We study stochastically forced semilinear parabolic PDE's of the Ginzburg-Landau type. The class of forcings considered are white noises in time and colored smooth noises in space. Existence of the dynamics in $L^\infty$, as well as…

Chaotic Dynamics · Physics 2009-10-31 J. -P. Eckmann , M. Hairer

We study unconstrained optimization problems of nonsmooth, nonconvex Lipschitz functions, using only noisy pairwise comparisons governed by a known link function. Our goal is to compute a $(\delta,\varepsilon)$-Goldstein stationary point.…

Optimization and Control · Mathematics 2026-02-10 Taha El Bakkali , El Mahdi Chayti , Omar Saadi

As represented by the Liouville measure, Gaussian multiplicative chaos is a random measure constructed from a Gaussian field. Under certain technical assumptions, we prove the convergence of a process time-changed by Gaussian multiplicative…

Probability · Mathematics 2024-10-02 Takumu Ooi

Let $M$ be a compact 1-manifold. Given a continuous function $g:M\to \mathbb R_+$ we consider the following ordinary differential equation: $\|\dot{f}(t)\|=g(t)$, where $f:M\to \mathbb R^2$. We construct a probability measure on the space…

Probability · Mathematics 2016-05-11 Amites Dasgupta , Mahuya Datta

We generalize the proof of Karamata's Theorem by the method of approximation by polynomials to the operator case. As a consequence, we offer a simple proof of \emph{uniform dual ergodicity} for a very large class of dynamical systems with…

Dynamical Systems · Mathematics 2014-12-09 Ian Melbourne , Dalia Terhesiu

We present a complete characterization of the metric compactification of $L_{p}$ spaces for $1\leq p < \infty$. Each element of the metric compactification of $L_{p}$ is represented by a random measure on a certain Polish space. By way of…

Functional Analysis · Mathematics 2022-06-01 Armando W. Gutiérrez

The convergence rate in Wasserstein distance is estimated for empirical measures of ergodic Markov processes, and the estimate can be sharp in some specific situations. The main result is applied to subordinations of typical models excluded…

Probability · Mathematics 2024-08-14 Feng-Yu Wang

We derive quantitative bounds on the rate of convergence in $L^1$ Wasserstein distance of general M-estimators, with an almost sharp (up to a logarithmic term) behavior in the number of observations. We focus on situations where the…

Statistics Theory · Mathematics 2021-11-19 François Bachoc , Max Fathi

We consider the sparse polynomial approximation of a multivariate function on a tensor product domain from samples of both the function and its gradient. When only function samples are prescribed, weighted $\ell^1$ minimization has recently…

Numerical Analysis · Mathematics 2019-02-22 Ben Adcock , Yi Sui

We introduce a sharpness functional for probabilistic models that quantifies sharpness as an intrinsic property of the probability distribution. The measure is derived based on a rank-based concentration principle that tracks upward…

Methodology · Statistics 2026-04-03 Pekka Syrjänen

We consider a nonparametric Bayesian approach to estimation and testing for a multivariate monotone density. Instead of following the conventional Bayesian route of putting a prior distribution complying with the monotonicity restriction,…

Statistics Theory · Mathematics 2023-06-09 Kang Wang , Subhashis Ghosal

We study the rate of convergence of the empirical spectral distribution of products of independent non-Hermitian random matrices to the power of the Circular Law. The distance to the deterministic limit distribution will be measured in…

Probability · Mathematics 2021-04-12 Jonas Jalowy

In this work, we study large deviation properties of the covariance process in fully connected Gaussian deep neural networks. More precisely, we establish a large deviation principle (LDP) for the covariance process in a functional…

Probability · Mathematics 2025-05-14 Luisa Andreis , Federico Bassetti , Christian Hirsch

We consider polynomials $P_n$ orthogonal with respect to the weight $J_{\nu}$ on $[0,\infty)$, where $J_{\nu}$ is the Bessel function of order $\nu$. Asheim and Huybrechs considered these polynomials in connection with complex Gaussian…

Classical Analysis and ODEs · Mathematics 2019-03-22 Alfredo Deaño , Arno B. J. Kuijlaars , Pablo Román

Let $K \subset \mathbb{R}^{2}$ be a rotation and reflection free self-similar set satisfying the strong separation condition, with dimension $\dim K = s > 1$. Intersecting $K$ with translates of a fixed line, one can study the $(s -…

Dynamical Systems · Mathematics 2016-02-02 Tuomas Orponen

Let $M = G/H$ be a connected simply connected homogeneous manifold of a compact, not necessarily connected Lie group $G$. We will assume that the isotropy $H$-module $\mathfrak {g/h}$ has a simple spectrum, i.e. irreducible submodules are…

Differential Geometry · Mathematics 2013-05-17 Michail M. Graev
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