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One of the basic principles of Approximation Theory is that the quality of approximations increase with the smoothness of the function to be approximated. Functions that are smooth in certain subdomains will have good approximations in…

Numerical Analysis · Mathematics 2016-12-23 Licia Lenarduzzi , Robert Schaback

The projection onto the epigraph or a level set of a closed proper convex function can be achieved by finding a root of a scalar equation that involves the proximal operator as a function of the proximal parameter. This paper develops the…

Optimization and Control · Mathematics 2021-02-16 Michael P. Friedlander , Ariel Goodwin , Tim Hoheisel

The (delta-) normal cone to an arbitrary intersection of sublevel sets of proper, lower semicontinuous, and convex functions is characterized, using either epsilon-subdifferentials at the nominal point or exact subdifferentials at nearby…

Optimization and Control · Mathematics 2017-10-30 Abderrahim Hantoute , Anton Svensson

In this article we utilise abstract convexity theory in order to unify and generalize many different concepts from nonsmooth analysis. We introduce the concepts of abstract codifferentiability, abstract quasidifferentiability and abstract…

Optimization and Control · Mathematics 2018-10-03 M. V. Dolgopolik

Fractional derivatives are a well-studied generalization of integer order derivatives. Naturally, for optimization, it is of interest to understand the convergence properties of gradient descent using fractional derivatives. Convergence…

Optimization and Control · Mathematics 2024-06-05 Ashwani Aggarwal

We study the approximation of nonlinear operators between function spaces by transformers. Our approach is to lift functions to measures supported on their graphs and leverage a recently introduced measure-theoretic view of transformers. A…

Machine Learning · Computer Science 2026-05-19 Takashi Furuya , David Mis , Ivan Dokmanić , Maarten V. de Hoop , Matti Lassas

Optimization problems, generalized equations, and the multitude of other variational problems invariably lead to the analysis of sets and set-valued mappings as well as their approximations. We review the central concept of set-convergence…

Optimization and Control · Mathematics 2020-02-25 Johannes O. Royset

We analyze the constant step size subgradient method on nonsmooth, nonconvex functions. We identify geometric assumptions on the objective function under which i) its domain admits a partition (stratification) into smooth manifolds (strata)…

Optimization and Control · Mathematics 2026-04-21 Evgenii Chzhen , Sholom Schechtman

We show that gradient descent can converge to any local minimum of a smooth semi-algebraic function. This holds if the step sizes are nonsummable and sufficiently small. The same results hold for the subgradient method on locally Lipschitz…

Optimization and Control · Mathematics 2026-02-27 Cédric Josz , Wenqing Ouyang

In this paper we consider the question of smoothness of slowly varying functions satisfying the modern definition that, in the last two decades, gained prevalence in the applications concerning function spaces and interpolation. We show,…

General Mathematics · Mathematics 2025-11-06 Dalimil Peša

Level-based and share-based loss functions are asymptotically equivalent if, in the limit, their averages converge almost surely to a constant ratio. These loss functions take a target value and its realization as arguments and are often…

Statistics Theory · Mathematics 2025-11-20 Charles D. Coleman

We consider topological dynamical systems over $\ZZ$ and, more generally, locally compact, $\sigma$-compact abelian groups. We relate spectral theory and diffraction theory. We first use a a recently developed general framework of…

Dynamical Systems · Mathematics 2018-09-21 Daniel Lenz

This paper presents a complete classification of minimal graph surfaces that admit graphical transformations into other minimal surfaces. These transformations are functions that map the height function of a minimal graph surface to another…

Differential Geometry · Mathematics 2026-01-26 Sam K Mathew

In this paper we address the convergence of stochastic approximation when the functions to be minimized are not convex and nonsmooth. We show that the "mean-limit" approach to the convergence which leads, for smooth problems, to the ODE…

Optimization and Control · Mathematics 2018-05-08 Szymon Majewski , Błażej Miasojedow , Eric Moulines

Steepest descent is central in variational mathematics. We present a new transparent existence proof for curves of near-maximal slope --- an influential notion of steepest descent in a nonsmooth setting. We moreover show that for…

Optimization and Control · Mathematics 2013-05-08 D. Drusvyatskiy , A. D. Ioffe , A. S. Lewis

Subdifferentials (in the sense of convex analysis) of matrix-valued functions defined on $\mathbb{R}^d$ that are convex with respect to the L\"{o}wner partial order can have a complicated structure and might be very difficult to compute…

Optimization and Control · Mathematics 2024-07-22 M. V. Dolgopolik

A hypodifferential is a compact family of affine mappings that defines a local max-type approximation of a nonsmooth convex function. We present a general theory of hypodifferentials of nonsmooth convex functions defined on a Banach space.…

Optimization and Control · Mathematics 2025-03-28 M. V. Dolgopolik

We give the theorem of coincidence of a class of functions defined by a generalised modulus of smoothness with a class of functions defined by the order of the best approximation by algebraic polynomials. We also prove the appropriate…

Functional Analysis · Mathematics 2012-08-28 Faton M. Berisha

In a well-known paper by Bruna, Nagel and Wainger [BNW], Fourier transform decay estimates were proved for smooth hypersurfaces of finite line type bounding a convex domain. In this paper, we generalize their results in the following ways.…

Classical Analysis and ODEs · Mathematics 2024-10-01 Michael Greenblatt

We give an example of a convex, finite and lower semicontinuous function whose subdifferential is everywhere empty. This is possible since the function is defined on an incomplete normed space. The function serves as a universal…

Optimization and Control · Mathematics 2024-09-30 Gerd Wachsmuth
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