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A new iterative technique is presented for solving of initial value problem for certain classes of multidimensional linear and nonlinear partial differential equations. Proposed iterative scheme does not require any discretization,…

Numerical Analysis · Mathematics 2016-02-23 Josef Rebenda , Zdeněk Šmarda

Set-valued classification, a new classification paradigm that aims to identify all the plausible classes that an observation belongs to, can be obtained by learning the acceptance regions for all classes. Many existing set-valued…

Machine Learning · Statistics 2022-09-22 Zhou Wang , Xingye Qiao

This monograph, written for educational purposes, serves as an introduction to the concept of integrability as it applies to systems of differential equations (both ordinary and partial) as well as to vector-valued fields. The general cases…

General Mathematics · Mathematics 2019-10-11 C. J. Papachristou

Extension problems for polynomial valuations on different cones of convex functions are investigated. It is shown that for the classes of functions under consideration, the extension problem reduces to a simple geometric obstruction on the…

Functional Analysis · Mathematics 2024-08-14 Jonas Knoerr , Jacopo Ulivelli

Initial-boundary value problems for nonlinear dispersive equations of evolution of order $2l+1,\;l\in\mathbb{N}$ with a convective term of the form $u^ku_x,\;k\in\mathbb{N}$ have been considered on intervals $(0,L),\;L\in (0,+\infty)$. The…

Analysis of PDEs · Mathematics 2018-12-12 Jackson Luchesi , Nikolai A. Larkin

By means of variational methods we establish existence and multiplicity of solutions for a class of nonlinear nonlocal problems involving the fractional p-Laplacian and a combined Sobolev and Hardy nonlinearity at subcritical and critical…

Analysis of PDEs · Mathematics 2018-02-19 Wenjing Chen , Sunra Mosconi , Marco Squassina

We investigate a family of approximate multi-step proximal point methods, framed as implicit linear discretizations of gradient flow. The resulting methods are multi-step proximal point methods, with similar computational cost in each…

Optimization and Control · Mathematics 2025-01-15 Yushen Huang , Yifan Sun

Nonuniform exponential dichotomy serves as an important characteristic of nonuniform hyperbolicity, while admissibility of function classes is often used to characterize nonuniform exponential dichotomy. In this paper, we investigate the…

Dynamical Systems · Mathematics 2026-03-12 Jiawei He , Jianhua Huang

Nonlinear two-point boundary value problems arise in numerous areas of application. The existence and number of solutions for various cases has been studied from a theoretical standpoint. These results generally rely upon growth conditions…

Numerical Analysis · Mathematics 2007-05-23 E. L. Allgower , D. J. Bates , A. J. Sommese , C. W. Wampler

In this paper, we discuss multiscale methods for nonlinear problems. The main idea of these approaches is to use local constraints and solve problems in oversampled regions for constructing macroscopic equations. These techniques are…

Numerical Analysis · Mathematics 2019-04-01 Wing T. Leung , Eric T. Chung , Yalchin Efendiev , Mary F. Wheeler

Topology identification and inference of processes evolving over graphs arise in timely applications involving brain, transportation, financial, power, as well as social and information networks. This chapter provides an overview of graph…

Signal Processing · Electrical Eng. & Systems 2025-12-12 Gonzalo Mateos , Yanning Shen , Georgios B. Giannakis , Ananthram Swami

We address the problem of classification of integrable differential-difference equations in 2+1 dimensions with one/two discrete variables. Our approach is based on the method of hydrodynamic reductions and its generalisation to dispersive…

Exactly Solvable and Integrable Systems · Physics 2015-06-15 E. V. Ferapontov , V. S. Novikov , I. Roustemoglou

We present pointwise gradient bounds for solutions to $p$-Laplacean type non-homogeneous equations employing non-linear Wolff type potentials, and then prove similar bounds, via suitable caloric potentials, for solutions to parabolic…

Analysis of PDEs · Mathematics 2009-12-02 Frank Duzaar , Giuseppe Mingione

The proximal gradient method is a generic technique introduced to tackle the non-smoothness in optimization problems, wherein the objective function is expressed as the sum of a differentiable convex part and a non-differentiable…

Numerical Analysis · Mathematics 2024-01-19 Abdeslem Hafid Bentbib , Khalide Jbilou , Ridwane Tahiri

Our main contributions include proving sufficient conditions for the existence of solution to a second order problem with nonzero nonlocal initial conditions, and providing a comprehensive analysis using fundamental solutions and…

Analysis of PDEs · Mathematics 2026-05-06 Sajid Ullah , Vittorio Colao

This article demonstrates how variation of parameters can be successfully implemented in combination with other classical techniques, such as the method of characteristics, to derive novel classes of solutions to nonlinear partial…

Analysis of PDEs · Mathematics 2025-05-13 Noureddine Mhadhbi , Sameh Gana , Mazen Fawaz Alsaeedi

Gaussian Process (GP) models are a powerful tool in probabilistic machine learning with a solid theoretical foundation. Thanks to current advances, modeling complex data with GPs is becoming increasingly feasible, which makes them an…

Machine Learning · Computer Science 2025-03-04 Sarem Seitz

We discuss to what extent the local techniques of resolution of singularities over fields of characteristic zero can be applied to improve singularities in general. For certain interesting classes of singularities, this leads to an embedded…

Algebraic Geometry · Mathematics 2018-01-22 Bernd Schober

We obtain exact solutions to the class of parabolic partial differential equations of arbitrary dimensionality and with arbitrary potentials. The solutions are presented in a compact-form: as explicit mathematical expressions consisting of…

Mathematical Physics · Physics 2023-08-29 Ivan Gonoskov

This paper considers networks where relationships between nodes are represented by directed dissimilarities. The goal is to study methods that, based on the dissimilarity structure, output hierarchical clusters, i.e., a family of nested…

Machine Learning · Computer Science 2016-07-22 Gunnar Carlsson , Facundo Mémoli , Alejandro Ribeiro , Santiago Segarra