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Let $\{X_n\}_{n\in\N}$ be a Markov chain on a measurable space $\X$ with transition kernel $P$ and let $V:\X\r[1,+\infty)$. The Markov kernel $P$ is here considered as a linear bounded operator on the weighted-supremum space $\cB_V$…

Probability · Mathematics 2013-12-06 Loïc Hervé , James Ledoux

We consider the problem of the approximation of the solution of a one-dimensional SDE with non-globally Lipschitz drift and diffusion coefficients behaving as $x^\alpha$, with $\alpha>1$. We propose an (semi-explicit) exponential-Euler…

Probability · Mathematics 2022-11-30 Mireille Bossy , Jean Francois Jabir , Kerlyns Martinez

For solving constrained (pseudo)-monotone variational inequality, we prove that the upper bound of stepsize $\frac{1}{2L}$ established for the Popov's algorithm and the forward-reflected-backward algorithm is tight. For unconstrained case,…

Optimization and Control · Mathematics 2026-03-09 Nhung Hong Nguyen , Thanh Quoc Trinh , Phan Tu Vuong

We present conservativeness criteria for sub-Markovian semigroups generated by divergence type operators with specified infinitesimally invariant measures. The conservativeness criteria in this article are derived by $L^1$-uniqueness and…

Probability · Mathematics 2022-08-16 Haesung Lee

A numerical analysis for the fully discrete approximation of an operator Lyapunov equation related to linear SPDEs (stochastic partial differential equations) driven by multiplicative noise is considered. The discretization of the Lyapunov…

Numerical Analysis · Mathematics 2022-05-04 Adam Andersson , Annika Lang , Andreas Petersson , Leander Schroer

In this paper, we prove convergence rates for time discretisation schemes for semi-linear stochastic evolution equations with additive or multiplicative Gaussian noise, where the leading operator $A$ is the generator of a strongly…

Numerical Analysis · Mathematics 2024-12-19 Katharina Klioba , Mark Veraar

We study diffusion processes corresponding to infinite dimensional semilinear stochastic differential equations with local Lipschitz drift term and an arbitrary Lipschitz diffusion coefficient. We prove tightness and the Feller property of…

Analysis of PDEs · Mathematics 2021-05-28 A. Es-Sarhir , M. Scheutzow , J. M. Tölle , O. van Gaans

For $\ell\colon \mathbb{R}^d \to [0,\infty)$ we consider the sequence of probability measures $\left(\mu_n\right)_{n \in \mathbb{N}}$, where $\mu_n$ is determined by a density that is proportional to $\exp(-n\ell)$. We allow for infinitely…

Probability · Mathematics 2023-12-11 Mareike Hasenpflug , Daniel Rudolf , Björn Sprungk

In this paper, we first explore exponential stability by using Monotonicity inequality and use this information to obtain the existence of Invariant measure for linear Stochastic PDEs with potential in the space of tempered distributions.…

Probability · Mathematics 2024-05-31 Arvind Kumar Nath

This paper deals with three major types of convergence of probability measures on metric spaces: weak convergence, setwise converges, and convergence in the total variation. First, it describes and compares necessary and sufficient…

Probability · Mathematics 2014-07-04 Eugene A. Feinberg , Pavlo O. Kasyanov , Michael Z. Zgurovsky

We study the long time behaviour of a Markov process evolving in $\mathbb{N}$ and conditioned not to hit 0. Assuming that the process comes back quickly from infinity, we prove that the process admits a unique quasi-stationary distribution…

Probability · Mathematics 2013-04-04 Servet Martinez , Jaime San Martin , Denis Villemonais

We propose a continuous-time formulation of persistent contrastive divergence (PCD) for maximum likelihood estimation (MLE) of unnormalised densities. Our approach expresses PCD as a coupled, multiscale system of stochastic differential…

Machine Learning · Statistics 2025-10-03 Paul Felix Valsecchi Oliva , O. Deniz Akyildiz , Andrew Duncan

Consider the ensemble of Real Symmetric Toeplitz Matrices, each entry iidrv from a fixed probability distribution p of mean 0, variance 1, and finite higher moments. The limiting spectral measure (the density of normalized eigenvalues)…

Probability · Mathematics 2010-11-16 Christopher Hammond , Steven J. Miller

We consider a stochastic conservation law on the line with solution-dependent diffusivity, a super-linear, sub-quadratic Hamiltonian, and smooth, spatially-homogeneous kick-type random forcing. We show that this Markov process admits a…

Probability · Mathematics 2023-08-29 Theodore D. Drivas , Alexander Dunlap , Cole Graham , Joonhyun La , Lenya Ryzhik

This paper presents some new criteria for partial exponential stability of a slow-fast nonlinear system with a fast scalar variable using periodic averaging methods. Unlike classical averaging techniques, we construct an averaged system by…

Systems and Control · Electrical Eng. & Systems 2019-10-17 Yuzhen Qin , Yu Kawano , Brian D. O. Anderson , Ming Cao

This thesis studies high-dimensional, continuous-valued pairwise Markov Random Fields. We are particularly interested in approximating pairwise densities whose logarithm belongs to a Sobolev space. For this problem we propose the method of…

Statistics Theory · Mathematics 2015-06-12 Eric Janofsky

Let $Q$ be a transition probability on a measurable space $E$, let $(X\_n)\_n$ be a Markov chain associated to $Q$, and let $\xi$ be a real-valued measurable function on $E$, and $S\_n = \sum\_{k=1}^{n} \xi(X\_k)$. Under functional…

Probability · Mathematics 2007-05-23 Loïc Hervé

Under the Ornstein-Uhlenbeck semigroup $\{U_t\}$, any non-negative measurable $f : \mathbb R^n \to \mathbb R_+$ exhibits a uniform tail bound better than that implied by Markov's inequality and conservation of mass: For every $\alpha \geq…

Probability · Mathematics 2018-05-23 Ronen Eldan , James R. Lee

We consider the classical Shiryaev--Roberts martingale diffusion, $(R_t)_{t\ge0}$, restricted to the interval $[0,A]$, where $A>0$ is a preset absorbing boundary. We take yet another look at the well-known phenomenon of quasi-stationarity…

Statistics Theory · Mathematics 2023-10-31 Soumik Banerjee , Aleksey S. Polunchenko

The estimation law of unknown parameters vector ${\theta}$ is proposed for one class of nonlinearly parametrized regression equations $y\left( t \right) = \Omega \left( t \right)\Theta \left( \theta \right)$. We restrict our attention to…

Systems and Control · Electrical Eng. & Systems 2023-08-22 Anton Glushchenko , Konstantin Lastochkin
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