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In this paper, we use the truncated EM method to study the finite time strong convergence for the SDEs with Poisson jumps under the Khasminskii-type condition. We establish the finite time $ \mathcal L ^r (r \ge 2) $ convergence rate when…

Numerical Analysis · Mathematics 2018-05-30 Shounian Deng , Weiyin Fei , Wei Liu , Xuerong Mao

We study the Euler scheme for a stochastic differential equation driven by a Levy process Y. More precisely, we look at the asymptotic behavior of the normalized error process u_n(X^n-X), where X is the true solution and X^n is its Euler…

Probability · Mathematics 2007-05-23 Jean Jacod

This paper focuses on the numerical scheme for multiple-delay stochastic differential equations with partially H\"older continuous drifts and locally H\"older continuous diffusion coefficients. To handle with the superlinear terms in…

Numerical Analysis · Mathematics 2024-03-19 Zhuoqi Liu , Zhaohang Wang , Siying Sun , Shuaibin Gao

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

We analyze the convergence behavior of stochastic gradient descent with momentum (SGDM) under dynamic learning-rate and batch-size schedules by introducing a novel and simpler Lyapunov function. We extend the existing theoretical framework…

Machine Learning · Computer Science 2025-10-13 Yuichi Kondo , Hideaki Iiduka

The problem of sampling a target probability distribution on a constrained domain arises in many applications including machine learning. For constrained sampling, various Langevin algorithms such as projected Langevin Monte Carlo (PLMC),…

Machine Learning · Statistics 2026-04-07 Yingli Wang , Changwei Tu , Xiaoyu Wang , Lingjiong Zhu

The strong convergence of Euler approximations of stochastic delay differential equations is proved under general conditions. The assumptions on drift and diffusion coefficients have been relaxed to include polynomial growth and only…

Probability · Mathematics 2013-03-07 Chaman Kumar , Sotirios Sabanis

The Euler-Maruyama scheme is known to diverge strongly and numerically weakly when applied to nonlinear stochastic differential equations (SDEs) with superlinearly growing and globally one-sided Lipschitz continuous drift coefficients.…

Probability · Mathematics 2015-03-19 Martin Hutzenthaler , Arnulf Jentzen , Peter E. Kloeden

This work establishes the weak convergence of Euler-Maruyama's approximation for stochastic differential equations (SDEs) with singular drifts under the integrability condition in lieu of the widely used growth condition. This method is…

Probability · Mathematics 2018-08-23 Jinghai Shao

In this paper, we study numerical approximations for stochastic differential equations (SDEs) that use adaptive step sizes. In particular, we consider a general setting where decisions to reduce step sizes are allowed to depend on the…

Numerical Analysis · Mathematics 2025-12-10 James Foster , Andraž Jelinčič

This study focuses on approximating solutions to SDEs driven by L\'evy processes with H\"older continuous drifts using the Euler-Maruyama scheme. We derive the $L^p$-error for a broad range of driven noises, including all nondegenerate…

Probability · Mathematics 2023-04-28 Yanfang Li , Guohuan Zhao

We consider the explicit numerical approximations of stochastic differential equations (SDEs) driven by Brownian process and Poisson jump. It is well known that under non-global Lipschitz condition, Euler Explicit method fails to converge…

Numerical Analysis · Mathematics 2018-02-21 Antoine Tambue , Jean Daniel Mukam

This paper proposes an adaptive timestep construction for an Euler-Maruyama approximation of SDEs with a drift which is not globally Lipschitz. It is proved that if the timestep is bounded appropriately, then over a finite time interval the…

Numerical Analysis · Mathematics 2016-09-27 Wei Fang , Michael Bryce Giles

We propose a new explicit numerical scheme for stochastic differential equation with super-linearly growing drift and linearly growing diffusion coefficients which are also twice continuously differentiable. The rate of strong convergence…

Probability · Mathematics 2018-06-04 Tejinder Kumar , Chaman Kumar

We are interested in the strong convergence and almost sure stability of Euler-Maruyama (EM) type approximations to the solutions of stochastic differential equations (SDEs) with non-linear and non-Lipschitzian coefficients. Motivation…

Numerical Analysis · Mathematics 2012-04-10 Xuerong Mao , Lukasz Szpruch

This article introduces and analyzes a new explicit, easily implementable, and full discrete accelerated exponential Euler-type approximation scheme for additive space-time white noise driven stochastic partial differential equations…

Probability · Mathematics 2020-06-04 Martin Hutzenthaler , Arnulf Jentzen , Diyora Salimova

This paper presents a strong convergence rate analysis of general discretization approximations for McKean-Vlasov SDEs with super-linear growth coefficients over infinite time horizon. Under some specified non-globally Lipschitz conditions,…

Numerical Analysis · Mathematics 2025-09-12 Taiyuan Liu , Yaozhong Hu , Siqing Gan

In this paper, we consider a class of stochastic differential equations driven by symmetric non-degenerate $\alpha$-stable processes (including cylindrical ones) with $\alpha \in (1,2)$. We first establish a quantitative estimate for the…

Probability · Mathematics 2026-04-10 Zimo Hao , Mingyan Wu

In this paper we study jump-diffusion stochastic differential equations (SDEs) with a discontinuous drift coefficient and a possibly degenerate diffusion coefficient. Such SDEs appear in applications such as optimal control problems in…

Numerical Analysis · Mathematics 2021-01-15 Paweł Przybyłowicz , Michaela Szölgyenyi

This paper is concerned with the numerical approximation of stochastic mechanical systems with nonlinear holonomic constraints. Such systems are described by second order stochastic differential-algebraic equations involving an implicitly…

Probability · Mathematics 2017-09-26 Felix Lindner , Holger Stroot
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