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We show how Lasry-Lions's result on regularization of functions defined on $\mathbb{R}^n$ or on Hilbert spaces by sup-inf convolutions with squares of distances can be extended to (finite or infinite dimensional) Riemannian manifolds $M$ of…

Differential Geometry · Mathematics 2014-01-21 Daniel Azagra , Juan Ferrera

We present here a new method for approximating functions defined on superreflexive Banach spaces by differentiable functions with $\alpha$-H\"older derivatives (for some $0<\alpha\leq 1$). The smooth approximation is given by means of an…

Functional Analysis · Mathematics 2016-09-07 Manuel Cepedello Boiso

The main goal of this paper is to present results of existence and non-existence of convex functions on Riemannian manifolds and, in the case of the existence, we associate such functions to the geometry of the manifold. Precisely, we prove…

Differential Geometry · Mathematics 2016-12-13 J. X. Cruz Neto , Ítalo Melo , Paulo Sousa

In this note we provide a full conjugacy and subdifferential calculus for convex convex-composite functions in finite-dimensional space. Our approach, based on infimal convolution and cone-convexity, is straightforward and yields the…

Optimization and Control · Mathematics 2019-08-22 James V. Burke , Tim Hoheisel , Quang V. Nguyen

Let $U\subseteq\mathbb{R}^{n}$ be open and convex. We show that every (not necessarily Lipschitz or strongly) convex function $f:U\to\mathbb{R}$ can be approximated by real analytic convex functions, uniformly on all of $U$. In doing so we…

Functional Analysis · Mathematics 2012-01-17 D. Azagra

Let $U\subseteq\mathbb{R}^d$ be open and convex. We prove that every (not necessarily Lipschitz or strongly) convex function $f:U\to\mathbb{R}$ can be approximated by real analytic convex functions, uniformly on all of $U$. We also show…

Differential Geometry · Mathematics 2014-10-24 Daniel Azagra

We consider the proximal gradient method on Riemannian manifolds for functions that are possibly not geodesically convex. Starting from the forward-backward-splitting, we define an intrinsic variant of the proximal gradient method that uses…

Optimization and Control · Mathematics 2025-06-12 Ronny Bergmann , Hajg Jasa , Paula John , Max Pfeffer

In this paper we introduce the class of infinite infimal convolution functionals and apply these functionals to the regularization of ill-posed inverse problems. The proposed regularization involves an infimal convolution of a continuously…

Optimization and Control · Mathematics 2024-12-17 Kristian Bredies , Marcello Carioni , Martin Holler , Yury Korolev , Carola-Bibiane Schönlieb

This paper considers projection and convolution operations for integrally convex functions, which constitute a fundamental function class in discrete convex analysis. It is shown that the class of integrally convex functions is stable under…

Optimization and Control · Mathematics 2018-08-09 Satoko Moriguchi , Kazuo Murota

We show that $C^0$-fine approximation of convex functions by smooth (or real analytic) convex functions on $\R^d$ is possible in general if and only if $d=1$. Nevertheless, for $d\geq 2$ we give a characterization of the class of convex…

Classical Analysis and ODEs · Mathematics 2012-01-24 Daniel Azagra

We consider abstract operator equations $Fu=y$, where $F$ is a compact linear operator between Hilbert spaces $U$ and $V$, which are function spaces on \emph{closed, finite dimensional Riemannian manifolds}, respectively. This setting is of…

Numerical Analysis · Mathematics 2015-05-28 Nicolas Thorstensen , Otmar Scherzer

In this work, we introduce a new class of non-convex functions, called implicit concave functions, which are compositions of a concave function with a continuously differentiable mapping. We analyze the properties of their minimization by…

Optimization and Control · Mathematics 2025-10-08 Vittorio Latorre

We study some basic properties of the function $f_0:M\rightarrow\IR$ on Hadamard manifolds defined by $$ f_0(x):=\langle u_0,\exp_{x_0}^{-1}x\rangle\quad\mbox{for any $x\in M$}. $$ A characterization for the function to be linear affine is…

Optimization and Control · Mathematics 2015-10-06 Xiangmei Wang , Chong Li , Jen-Chih Yao

We consider minimization of functions that are compositions of convex or prox-regular functions (possibly extended-valued) with smooth vector functions. A wide variety of important optimization problems fall into this framework. We describe…

Optimization and Control · Mathematics 2015-04-24 A. S. Lewis , S. J. Wright

We establish a second order smooth variational principle valid for functions defined on (possibly infinite-dimensional) Riemannian manifolds which are uniformly locally convex and have a strictly positive injectivity radius and bounded…

Differential Geometry · Mathematics 2007-05-23 Daniel Azagra , Robb Fry

Using the convex functions in Grassmannian manifolds we can carry out interior estimates for mean curvature flow of higher codimension. In this way some of the results of Ecker-Huisken can be generalized to higher codimension

Differential Geometry · Mathematics 2008-07-10 Y. L. Xin , Ling Yang

This paper is devoted to the study of non-existence of certain type of convex functions on a Riemannian manifold with a pole. To this end, we have developed the notion of odd and even function on a Riemannian manifold with a pole and proved…

Differential Geometry · Mathematics 2019-07-08 Absos Ali Shaikh , Chandan Kumar Mondal , Izhar Ahmad

This paper addresses a class of nonsmooth and nonconvex optimization problems defined on complete Riemannian manifolds. The objective function has a composite structure, combining convex, differentiable, and lower semicontinuous terms,…

Optimization and Control · Mathematics 2025-11-19 Vitaliano S. Amaral , Marcio Antônio de A. Bortoloti , Jurandir O. Lopes , Gilson N. Silva

In this paper, we study a family of non-convex and possibly non-smooth inf-projection minimization problems, where the target objective function is equal to minimization of a joint function over another variable. This problem include…

Machine Learning · Computer Science 2020-07-15 Yan Yan , Yi Xu , Lijun Zhang , Xiaoyu Wang , Tianbao Yang

On a manifold we term a hypersurface foliation a slicing if it is the level set foliation of a slice function -- meaning some real valued function $f$ satisfying that $df$ is nowhere zero. On Riemannian manifolds we give a non-linear PDE on…

Differential Geometry · Mathematics 2023-12-21 A. Rod Gover , Valentina-Mira Wheeler
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