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Large-scale optimization problems require algorithms both effective and efficient. One such popular and proven algorithm is Stochastic Gradient Descent which uses first-order gradient information to solve these problems. This paper studies…

Optimization and Control · Mathematics 2021-11-11 Theodoros Mamalis , Dusan Stipanovic , Petros Voulgaris

Strong convergence results on tamed Euler schemes, which approximate stochastic differential equations with superlinearly growing drift coefficients that are locally one-sided Lipschitz continuous, are presented in this article. The…

Probability · Mathematics 2013-06-17 Sotirios Sabanis

This paper studies iterative schemes for measure transfer and approximation problems, which are defined through a slicing-and-matching procedure. Similar to the sliced Wasserstein distance, these schemes benefit from the availability of…

Numerical Analysis · Mathematics 2026-03-17 Shiying Li , Caroline Moosmueller , Yongzhe Wang

In this article, a three-time levels compact scheme is proposed to solve the partial integro-differential equation governing the option prices under jump-diffusion models. In the proposed compact scheme, the second derivative approximation…

Computational Finance · Quantitative Finance 2018-04-23 Kuldip Singh Patel , Mani Mehra

L\'{e}vy flight models whose jumps have infinite moments are mathematically used to describe the superdiffusion in complex systems. Exponentially tempering the Levy measure of L\'{e}vy flights leads to the tempered stable L\'{e}vy processes…

Computational Physics · Physics 2016-05-19 Can Li , Weihua Deng

We introduce a class of adaptive timestepping strategies for stochastic differential equations with non-Lipschitz drift coefficients. These strategies work by controlling potential unbounded growth in solutions of a numerical scheme due to…

Numerical Analysis · Mathematics 2016-10-14 Cónall Kelly , Gabriel J. Lord

This paper is devoted to order-one explicit approximations of random periodic solutions to multiplicative noise driven stochastic differential equations (SDEs) with non-globally Lipschitz coefficients. The existence of the random periodic…

Probability · Mathematics 2025-01-06 Yujia Guo , Xiaojie Wang , Yue Wu

This paper studies open-loop equilibriums for a general class of time-inconsistent stochastic control problems under jump-diffusion SDEs with deterministic coefficients. Inspired by the idea of Four-Step-Scheme for forward-backward…

Optimization and Control · Mathematics 2020-08-18 Ishak Alia

In this paper we extend existing results on the numerical approximation of one-dimensional SDEs with drift in a negative order Besov space and driven by Brownian motion. Using the Yamada-Watanabe approximation technique, we prove rates in…

Probability · Mathematics 2026-02-03 Matteo Cagnotti

We study the convergence rates of the semi-discrete (SD) method originally proposed in Halidias (2012), Semi-discrete approximations for stochastic differential equations and applications, International Journal of Computer Mathematics,…

Numerical Analysis · Mathematics 2020-05-06 Ioannis S. Stamatiou , Nikolaos Halidias

We present new high-order Alternating Direction Implicit (ADI) schemes for the numerical solution of initial-boundary value problems for convection-diffusion equations with mixed derivative terms. Our approach is based on the…

Numerical Analysis · Mathematics 2015-05-29 Bertram Düring , Michel Fournié , Alain Rigal

In this work, we consider the numerical solution of an initial boundary value problem for the distributed order time fractional diffusion equation. The model arises in the mathematical modeling of ultra-slow diffusion processes observed in…

Numerical Analysis · Mathematics 2015-04-08 Bangti Jin , Raytcho Lazarov , Dongwoo Sheen , Zhi Zhou

This work aims to estimate the drift and diffusion functions in stochastic differential equations (SDEs) driven by a particular class of L\'evy processes with finite jump intensity, using neural networks. We propose a framework that…

Machine Learning · Statistics 2025-07-10 Jose-Hermenegildo Ramirez-Gonzalez , Ying Sun

This paper first establishes a fundamental mean-square convergence theorem for general one-step numerical approximations of L\'{e}vy noise driven stochastic differential equations with non-globally Lipschitz coefficients. Then two novel…

Numerical Analysis · Mathematics 2019-07-24 Ziheng Chen , Siqing Gan , Xiaojie Wang

In this article, we propose a Milstein finite difference scheme for a stochastic partial differential equation (SPDE) describing a large particle system. We show, by means of Fourier analysis, that the discretisation on an unbounded domain…

Numerical Analysis · Mathematics 2012-04-09 Michael B. Giles , Christoph Reisinger

In this paper we study the convergence of a Lie-Trotter operator splitting for stochastic semi-linear evolution equations in a Hilbert space. The abstract Hilbert space setting allows for the consideration of convergence of the…

Numerical Analysis · Mathematics 2024-12-20 Joshua L Padgett , Qin Sheng

In this paper, we present a discrete-type approximation scheme to solve continuous-time optimal stopping problems based on fully non-Markovian continuous processes adapted to the Brownian motion filtration. The approximations satisfy…

Probability · Mathematics 2019-06-24 Dorival Leão , Alberto Ohashi , Francesco Russo

A higher-order numerical method is presented for scalar valued, coupled forward-backward stochastic differential equations. Unlike most classical references, the forward component is not only discretized by an Euler-Maruyama approximation…

Numerical Analysis · Mathematics 2025-01-22 Balint Negyesi , Cornelis W. Oosterlee

In this paper, we investigate the optimal control problems for stochastic differential equations (SDEs in short) of mean-field type with jump processes. The control variable is allowed to enter into both diffusion and jump terms. This…

Optimization and Control · Mathematics 2013-02-27 Mokhtar Hafayed , Syed Abbas

The aim of this note is to propose a novel numerical scheme for drift-less one dimensional stochastic differential equations of It\^o's type driven by standard Brownian motion. Our approximation method is equivalent to the well known…

Probability · Mathematics 2024-07-24 Alberto Lanconelli , Berk Tan Perçin