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We propose and analyze a regularization approach for structured prediction problems. We characterize a large class of loss functions that allows to naturally embed structured outputs in a linear space. We exploit this fact to design…

Machine Learning · Computer Science 2017-07-31 Carlo Ciliberto , Alessandro Rudi , Lorenzo Rosasco

In this paper we investigate an adaptive discretization strategy for ill-posed linear prob- lems combined with a regularization from a class of semiiterative methods. We show that such a discretization approach in combination with a…

Numerical Analysis · Mathematics 2014-07-22 Wolfgang Erb , Evgeniya V. Semenova

We present a short review of the evolution of the methodology of the Method of simplest equation for obtaining exact particular solutions of nonlinear partial differential equations (NPDEs) and the recent extension of a version of this…

Exactly Solvable and Integrable Systems · Physics 2019-06-20 Nikolay K. Vitanov

The numerical solution methods for partial differential equation (PDE) solution allow obtaining a discrete field that converges towards the solution if the method is applied to the correct problem. Nevertheless, the numerical methods…

Numerical Analysis · Mathematics 2021-03-04 Alexander Hvatov

In this article, we analyse the domain mapping method approach to approximate statistical moments of solutions to linear elliptic partial differential equations posed over random geometries including smooth surfaces and bulk-surface…

Numerical Analysis · Mathematics 2019-03-18 Lewis Church , Ana Djurdjevac , Charles M. Elliott

We overview results on the topic of Poisson approximation that are missed in existing surveys. The topic of Poisson approximation to the distribution of a sum of integer-valued random variables is presented as well. We do not restrict…

Probability · Mathematics 2019-04-12 S. Y. Novak

We use a numerical-analytic technique to construct a sequence of successive approximations to the solution of a system of fractional differential equations, subject to Dirichlet boundary conditions. We prove the uniform convergence of the…

Numerical Analysis · Mathematics 2022-09-05 Kateryna Marynets , Dona Pantova

An exact discretization method is being developed for solving linear systems of ordinary fractional-derivative differential equations with constant matrix coefficients (LSOFDDECMC). It is shown that the obtained linear discrete system in…

Dynamical Systems · Mathematics 2019-03-18 Fikret A. Aliev , N. A. Aliev , N. I. Velieva , K. G. Gasimova , Y. V Mamedova

We briefly review two different methods of applying Lie group theory in the numerical solution of ordinary differential equations. On specific examples we show how the symmetry preserving discretization provides difference schemes for which…

Mathematical Physics · Physics 2013-04-29 Decio Levi , Pavel Winternitz

This paper is concerned with approximations and related discretization error estimates for the normal derivatives of solutions of linear elliptic partial differential equations. In order to illustrate the ideas, we consider the Poisson…

Numerical Analysis · Mathematics 2018-04-17 J. Pfefferer , M. Winkler

Approximation techniques have been historically important for solving differential equations, both as initial value problems and boundary value problems. The integration of numerical, analytic and perturbation methods and techniques can…

Classical Analysis and ODEs · Mathematics 2025-02-25 J. Nathan Kutz

A new method for approximating fractional derivatives of the Gaussian function and Dawson's integral are presented. Unlike previous approaches, which are dominantly based on some discretization of Riemann-Liouville integral using polynomial…

Numerical Analysis · Mathematics 2017-09-08 Can Evren Yarman

A probabilistic representation for initial value semilinear parabolic problems based on generalized random trees has been derived. Two different strategies have been proposed, both requiring generating suitable random trees combined with a…

Numerical Analysis · Mathematics 2024-02-13 Juan A. Acebron , Angel Rodriguez-Rozas

We formulate a well-posedness and approximation theory for a class of generalised saddle point problems. In this way we develop an approach to a class of fourth order elliptic partial differential equations using the idea of splitting into…

Numerical Analysis · Mathematics 2019-04-02 Charles M. Elliott , Hans Fritz , Graham Hobbs

An efficient approximate version of implicit Taylor methods for initial-value problems of systems of ordinary differential equations (ODEs) is introduced. The approach, based on an approximate formulation of Taylor methods, produces a…

Numerical Analysis · Mathematics 2024-02-05 Antonio Baeza , Raimund Bürger , María del Carmen Martí , Pep Mulet , David Zorío

Stochastic versions of proximal methods have gained much attention in statistics and machine learning. These algorithms tend to admit simple, scalable forms, and enjoy numerical stability via implicit updates. In this work, we propose and…

Machine Learning · Statistics 2024-09-09 Haoyu Jiang , Jason Xu

In the article we discuss the notion of the generalized invariant manifold introduced in our previous study. In the literature the method of the differential constraints is well known as a tool for constructing particular solutions for the…

Exactly Solvable and Integrable Systems · Physics 2021-07-08 I. T. Habibullin , A. R. Khakimova , A. O. Smirnov

We give an algorithm for approximating a given plane curve segment by a planar elastic curve. The method depends on an analytic representation of the space of elastic curve segments, together with a geometric method for obtaining a good…

Numerical Analysis · Mathematics 2016-08-05 David Brander , Jens Gravesen , Toke Bjerge Nørbjerg

Diffuse domain methods (DDMs) have garnered significant attention for approximating solutions to partial differential equations on complex geometries. These methods implicitly represent the geometry by replacing the sharp boundary interface…

Analysis of PDEs · Mathematics 2025-04-25 Toai Luong , Tadele Mengesha , Steven M. Wise , Ming Hei Wong

Parametric model order reduction using reduced basis methods can be an effective tool for obtaining quickly solvable reduced order models of parametrized partial differential equation problems. With speedups that can reach several orders of…

Numerical Analysis · Mathematics 2022-01-26 Mario Ohlberger , Stephan Rave
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