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This paper gives a framework to produce the lower bound of eigenvalues defined in a Hilbert space by the eigenvalues defined in another Hilbert space. The method is based on using the max-min principle for the eigenvalue problems.

Numerical Analysis · Mathematics 2016-09-22 Hehu Xie , Chunguang You

We study a class of second-order boundary-degenerate elliptic equations in two dimensions with minimal regularity assumptions. We prove a maximum principle and a Harnack inequality at the degenerate boundary, and assuming local boundedness,…

Analysis of PDEs · Mathematics 2019-12-17 Brian Weber

We prove that for all smooth nonconstant initial data the initial-Neumann boundary value problem for the Perona-Malik equation in image processing possesses infinitely many Lipschitz weak solutions on smooth bounded convex domains in all…

Analysis of PDEs · Mathematics 2015-03-04 Seonghak Kim , Baisheng Yan

We consider Hessian quotient equations in Riemannian setting related to a problem posed by Delano\"e and Urbas. We prove unobstructed second order a priori estimate for the real Hessian quotient equation via the maximum principle argument…

Differential Geometry · Mathematics 2025-07-30 Marcin Sroka

This paper discusses a connection between scalar convex conservation laws and Pontryagin's minimum principle. For flux functions for which an associated optimal control problem can be found, a minimum value solution of the conservation law…

Numerical Analysis · Mathematics 2017-02-13 Wei Kang , Lucas C. Wilcox

We consider minimization of a smooth nonconvex function with inexact oracle access to gradient and Hessian (without assuming access to the function value) to achieve approximate second-order optimality. A novel feature of our method is that…

Optimization and Control · Mathematics 2024-03-27 Shuyao Li , Stephen J. Wright

A fundamental class of inferential problems are those characterised by there having been a substantial degree of pre-data (or prior) belief that the value of a model parameter was equal or lay close to a specified value, which may, for…

Other Statistics · Statistics 2021-01-26 Russell J. Bowater

In this paper we continue to advance the theory regarding the Riesz fractional gradient in the calculus of variations and fractional partial differential equations begun in an earlier work of the same name. In particular we here establish…

Functional Analysis · Mathematics 2016-11-23 Daniel Spector , Tien-Tsan Shieh

About thirty years ago we looked for "minimal assumptions" on the data which guarantee that solutions to the $\,2-D\,$ evolution Euler equations in a bounded domain are classical. Classical means here that all the derivatives appearing in…

Analysis of PDEs · Mathematics 2015-02-05 Hugo Beirao da Veiga

We extend Peng's maximum principle for semilinear stochastic partial differential equations (SPDEs) in one space-dimension with non-convex control domains and control-dependent diffusion coefficients to the case of general cost functionals…

Probability · Mathematics 2021-10-28 Wilhelm Stannat , Lukas Wessels

Comparison principles are developed for discrete quasilinear elliptic partial differential equations. We consider the analysis of a class of nonmonotone Leray-Lions problems featuring both nonlinear solution and gradient dependence in the…

Numerical Analysis · Mathematics 2017-11-02 Sara Pollock , Yunrong Zhu

Aleksandrov-Bakelman-Pucci maximum principles are studied for a class of fully nonlinear integro-differential equations of order $\sigma\in [2-\varepsilon_0,2)$, where $\varepsilon_0$ is a small constant depending only on given parameters.…

Analysis of PDEs · Mathematics 2022-07-15 Shuhei Kitano

In this paper, we present a rigorous framework for rational minimax approximation of matrix-valued functions that generalizes classical scalar approximation theory. Given sampled data $\{(x_\ell, {F}(x_\ell))\}_{\ell=1}^m$ where…

Numerical Analysis · Mathematics 2025-09-12 Lei-Hong Zhang , Ya-Nan Zhang , Chenkun Zhang , Shanheng Han

Hessian operators arising in inverse problems governed by partial differential equations (PDEs) play a critical role in delivering efficient, dimension-independent convergence for both Newton solution of deterministic inverse problems, as…

For any $\alpha $ small, we construct infinitely many $C^{1,\alpha}$ very weak solutions to the 2-Hessian equation with prescribed boundary value. The proof relies on the convex integration method and cut-off technique.

Analysis of PDEs · Mathematics 2025-09-29 Tongtong Li , Guohuan Qiu

We develop and analyze several different second-order algorithms for computing a near-optimal solution path of a convex parametric optimization problem with smooth Hessian. Our algorithms are inspired by a differential equation perspective…

Optimization and Control · Mathematics 2023-06-16 Heyuan Liu , Paul Grigas

The maximum principle is one of the most important tools in the analysis of geometric partial differential equations. Traditionally, the maximum principle is applied to a scalar function defined on a manifold, but in recent years more…

Differential Geometry · Mathematics 2014-02-18 S. Brendle

In bounded domains, without any geometric conditions, we study the existence and uniqueness of globally Lipschitz and interior strong C^{1,1}, (and classical C^2), solutions of general semilinear oblique boundary value problems for…

Analysis of PDEs · Mathematics 2018-12-05 Feida Jiang , Neil S Trudinger

A variational principle is introduced to provide a new formulation and resolution for several boundary value problems with a variational structure. This principle allows one to deal with problems well beyond the weakly compact structure. As…

Analysis of PDEs · Mathematics 2017-05-24 Abbas Moameni

A second-order regularity theory is developed for solutions to a class of quasilinear elliptic equations in divergence form, including the $p$-Laplace equation, with merely square-integrable right-hand side. Our results amount to the…

Analysis of PDEs · Mathematics 2018-05-23 Andrea Cianchi , Vladimir Maz'ya
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