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High-order methods gain increased attention in computational fluid dynamics. However, due to the time step restrictions arising from the semi-implicit time stepping for the incompressible case, the potential advantage of these methods…

Numerical Analysis · Mathematics 2019-10-02 Immo Huismann , Jörg Stiller , Jochen Fröhlich

In the present work, we delve into further study of numerical approximations of SDEs with non-globally monotone coefficients. We design and analyze a new family of stopped increment-tamed time discretization schemes of Euler, Milstein and…

Numerical Analysis · Mathematics 2024-10-08 Lei Dai , Xiaojie Wang

There are many methods for finding a particular solution to a nonhomogeneous linear ordinary differential equation (ODE) with constant coefficients. The method of undetermined coefficients, Laplace transform method and differential operator…

General Mathematics · Mathematics 2021-03-08 Jozef Fecenko

In this paper we consider splitting methods for the time integration of parabolic and certain classes of hyperbolic partial differential equations, where one partial flow can not be computed exactly. Instead, we use a numerical…

Numerical Analysis · Mathematics 2017-01-06 Lukas Einkemmer , Alexander Ostermann

First-order stochastic methods are the state-of-the-art in large-scale machine learning optimization owing to efficient per-iteration complexity. Second-order methods, while able to provide faster convergence, have been much less explored…

Machine Learning · Statistics 2017-12-01 Naman Agarwal , Brian Bullins , Elad Hazan

In this work, an approximate family of implicit multiderivative Runge-Kutta (MDRK) time integrators for stiff initial value problems is presented. The approximation procedure is based on the recent Approximate Implicit Taylor method (Baeza…

Numerical Analysis · Mathematics 2023-02-07 Jeremy Chouchoulis , Jochen Schütz

Gradient-based methods for optimisation of objectives in stochastic settings with unknown or intractable dynamics require estimators of derivatives. We derive an objective that, under automatic differentiation, produces low-variance…

Machine Learning · Computer Science 2019-09-25 Gregory Farquhar , Shimon Whiteson , Jakob Foerster

Conventional finite-difference schemes for solving partial differential equations are based on approximating derivatives by finite-differences. In this work, an alternative theory is proposed which view finite-difference schemes as…

Numerical Analysis · Mathematics 2013-09-23 Siu A. Chin

High-order clustering aims to identify heterogeneous substructures in multiway datasets that arise commonly in neuroimaging, genomics, social network studies, etc. The non-convex and discontinuous nature of this problem pose significant…

Methodology · Statistics 2022-10-11 Rungang Han , Yuetian Luo , Miaoyan Wang , Anru R. Zhang

We discuss the extent to which it is necessary to include higher-derivative operators in the effective field theory of general scalar-tensor theories. We explore the circumstances under which it is correct to restrict to second-order…

High Energy Physics - Theory · Physics 2018-02-28 Adam R. Solomon , Mark Trodden

Local search heuristics for non-convex optimizations are popular in applied machine learning. However, in general it is hard to guarantee that such algorithms even converge to a local minimum, due to the existence of complicated saddle…

Machine Learning · Computer Science 2016-02-19 Anima Anandkumar , Rong Ge

We describe an algorithm for the numerical solution of second order linear differential equations in the highly-oscillatory regime. It is founded on the recent observation that the solutions of equations of this type can be accurately…

Numerical Analysis · Mathematics 2015-06-23 James Bremer

We present an explicit 1-step numerical method of third order that is error-free on autonomous scalar Riccati equations such as the logistic equation. The method replaces the differential equation by its quadratic Taylor polynomial in each…

Numerical Analysis · Mathematics 2020-04-01 Thomas Krainer , Chenzhang Zhou

This paper presents a general framework of high-order finite difference (HFD) schemes for the tempered fractional Laplacian (TFL) based on new generating functions obtained from the discrete symbols. Specifically, for sufficiently smooth…

Numerical Analysis · Mathematics 2026-01-30 Mingyi Wang , Dongling Wang

This study proposes a high-order multi-scale method tailored for time-dependent nonlinear thermo-electro-mechanical coupling problems of composite structures with highly spatial heterogeneity, which incorporate temperature-dependent…

Numerical Analysis · Mathematics 2026-04-22 Hao Dong

We consider the problem of flexible modeling of higher order hidden Markov models when the number of latent states and the nature of the serial dependence, including the true order, are unknown. We propose Bayesian nonparametric methodology…

Methodology · Statistics 2019-02-06 Abhra Sarkar , David B. Dunson

In this paper, using the similarity method, we construct particular solutions with singularities for degenerate high-order equations. The considered equations have singularities of the first and second kind. Particular solutions are…

Analysis of PDEs · Mathematics 2020-05-06 B. Yu. Irgashev

In this paper, new Levin methods are presented for calculating oscillatory integrals with algebraic and/or logarithmic singularities. To avoid singularity, the technique of singularity separation is applied and then the singular ODE…

Numerical Analysis · Mathematics 2019-12-23 Yinkun Wang , Shuhuang Xiang

We introduce and analyze a family of heterogeneous multiscale methods for the numerical integration of highly oscillatory systems of delay differential equations with constant delays. The methodology suggested provides algorithms of…

Numerical Analysis · Mathematics 2018-12-03 M. P. Calvo , J. M. Sanz-Serna , Beibei Zhu

In this paper, we consider the problem of solving a constrained system of nonlinear equations. We propose an algorithm based on a combination of the Newton and conditional gradient methods, and establish its local convergence analysis. Our…

Optimization and Control · Mathematics 2016-08-25 Max L. N. Goncalves , Jefferson G. Melo
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