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The steepest descent method for multiobjective optimization on Riemannian manifolds with lower bounded sectional curvature is analyzed in this paper. The aim of the paper is twofold. Firstly, an asymptotic analysis of the method is…

Optimization and Control · Mathematics 2019-06-17 Orizon P. Ferreira , Maurício S. Louzeiro , Leandro F. Prudente

The present paper is concerned with Lipschitz properties of convex mappings. One considers the general context of mappings defined on an open convex subset $\Omega$ of a locally convex space $X$ and taking values in a locally convex space…

Functional Analysis · Mathematics 2017-01-12 S. Cobzaş

We propose a regularized Hessian-free Newton-type method for minimizing smooth convex functions with Lipschitz continuous Hessians. The algorithm constructs an approximate Hessian by finite differences and selects the regularization…

Optimization and Control · Mathematics 2026-05-01 Leandro Farias Maia , Antonio Victor B. Nascimento , Paulo Sergio M. Santos , Gilson N. Silva

We consider the classical gradient descent algorithm with constant stepsizes, where some error is introduced in the computation of each gradient. More specifically, we assume some relative bound on the inexactness, in the sense that the…

Optimization and Control · Mathematics 2025-09-12 Pierre Vernimmen , François Glineur

We provide sharp and explicit characterizations of the normal cone to sublevel sets of suprema of arbitrary functions, expressed exclusively in terms of subdifferentials of the data functions. In the convex case, the resulting formulas…

Optimization and Control · Mathematics 2026-02-12 Stephanie Caro , Rafael Correa , Abderrahim Hantoute

We construct Lipschitz $Q$-valued functions which approximate carefully integral currents when their cylindrical excess is small and they are almost minimizing in a suitable sense. This result is used in two subsequent works to prove the…

Analysis of PDEs · Mathematics 2016-06-13 Camillo De Lellis , Emanuele Spadaro , Luca Spolaor

An algorithm is proposed, analyzed, and tested for minimizing locally Lipschitz objective functions that may be nonconvex and/or nonsmooth. The algorithm, which is built upon the gradient-sampling methodology, is designed specifically for…

Optimization and Control · Mathematics 2026-04-02 Albert S. Berahas , Frank E. Curtis , Lara Zebiane

The goal of the paper is development of an optimization method with the superlinear convergence rate for a nonsmooth convex function. For optimization an approximation is used that is similar to the Steklov integral averaging. The…

Optimization and Control · Mathematics 2023-08-03 I. M. Prudnikov

We establish the first partial regularity result for local minima of strongly $\mathscr{A}$-quasiconvex integrals in the case where the differential operator $\mathscr{A}$ possesses an elliptic potential $\mathbb{A}$. As the main…

Analysis of PDEs · Mathematics 2020-09-30 Sergio Conti , Franz Gmeineder

On some specified convex supporting sets of spheres, we find a generalized longitude function whose level sets are totally geodesic. Given an arbitrary (weakly) harmonic map into spheres, the composition of the generalized longitude…

Differential Geometry · Mathematics 2013-07-09 Ling Yang

The goal of the paper is to study the particular class of regularly ${\mathcal{H}}$-convex functions, when ${\mathcal{H}}$ is the set ${\mathcal{L}\widehat{C}}(X,{\mathbb{R}})$ of real-valued Lipschitz continuous classically concave…

Optimization and Control · Mathematics 2022-08-03 Valentin V. Gorokhovik

We provide some counterexamples concerning the uniqueness and regularity of weak solutions to the initial-boundary value problem for gradient flows of certain strongly polyconvex functionals by showing that such a problem can possess a…

Analysis of PDEs · Mathematics 2022-05-17 Baisheng Yan

We prove partial regularity for minimizers of vectorial integrals of the Calculus of Variations, with general growth condition, imposing quasiconvexity assumptions only in an asymptotic sense.

Analysis of PDEs · Mathematics 2017-12-07 Teresa Isernia , Chiara Leone , Anna Verde

We study the local Lipschitz one subsets of a finite dimensional space, that is, sets for which there exists a continuous function whose local Lipschitz derivative is the characteristic function of said set. We give a characterization of a…

Functional Analysis · Mathematics 2026-04-22 Ziemowit M. Wójcicki

We establish regularity results for viscosity solutions to a class of quasilinear parabolic equations exhibiting nonhomogeneous degeneracy or singularity (a double phase regime) of the form \[ u_t - \big(|Du|^{\mathfrak{p}} +…

Analysis of PDEs · Mathematics 2026-04-28 Junior da Silva Bessa , João Vitor da Silva , Ginaldo de Santana Sá

For solving a broad class of nonconvex programming problems on an unbounded constraint set, we provide a self-adaptive step-size strategy that does not include line-search techniques and establishes the convergence of a generic approach…

Optimization and Control · Mathematics 2022-12-14 Thang Tran Ngoc , Hai Trinh Ngoc

The nonlinear semigroup generated by the subdifferential of a convex lower semicontinuous function $\varphi$ has a smoothing effect, discovered by H. Br\'ezis, which implies maximal regularity for the evolution equation. We use this and…

Analysis of PDEs · Mathematics 2019-11-13 Wolfgang Arendt , Daniel Hauer

Recent quasi-optimal error estimates for the finite element approximation of total-variation regularized minimization problems require the existence of a Lipschitz continuous dual solution. We discuss the validity of this condition and…

Numerical Analysis · Mathematics 2021-06-28 Sören Bartels , Robert Tovey , Friedrich Wassmer

The purpose of the paper is to give a complete characterization of the continuity of lower envelopes in the infinite dimensional spaces in terms of the notion of c-regularity. As an application we introduce a variational unconstrained…

Functional Analysis · Mathematics 2011-08-10 Nihat Gokhan Gogus

This paper presents an extension of stochastic gradient descent for the minimization of Lipschitz continuous loss functions. Our motivation is for use in non-smooth non-convex stochastic optimization problems, which are frequently…

Optimization and Control · Mathematics 2022-10-05 Michael R. Metel , Akiko Takeda