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Given a graphical model (GM), computing its partition function is the most essential inference task, but it is computationally intractable in general. To address the issue, iterative approximation algorithms exploring certain local…

Machine Learning · Computer Science 2019-05-15 Sejun Park , Eunho Yang , Se-Young Yun , Jinwoo Shin

This article is a review of functional $f(R)$ approximations in the asymptotic safety approach to quantum gravity. It mostly focusses on a formulation that uses a non-adaptive cutoff, resulting in a second order differential equation. This…

High Energy Physics - Theory · Physics 2022-10-21 Tim R. Morris , Dalius Stulga

The modeling of fracture problems within geometrically linear elasticity is often based on the space of generalized functions of bounded deformation $GSBD^p(\Omega)$, $p\in(1,\infty)$, their treatment is however hindered by the very low…

Analysis of PDEs · Mathematics 2019-12-13 Sergio Conti , Matteo Focardi , Flaviana Iurlano

Having a function $f$ and a set of functionals $\{\mathcal{C}_{n}\}$, $c_n^f \equiv \mathcal{C}_n \left(f\right)$, one can interpret function approximation very generally as a construction of some function $\mathcal{A}_{N}^{f}$ such that…

General Mathematics · Mathematics 2022-03-22 Andrej Liptaj

We propose a new length formula that governs the iterates of the momentum method when minimizing differentiable semialgebraic functions with locally Lipschitz gradients. It enables us to establish local convergence, global convergence, and…

Optimization and Control · Mathematics 2024-01-09 Cédric Josz , Lexiao Lai , Xiaopeng Li

We consider a composite optimization problem where the sum of a continuously differentiable and a merely lower semicontinuous function has to be minimized. The proximal gradient algorithm is the classical method for solving such a problem…

Optimization and Control · Mathematics 2023-05-01 Xiaoxi Jia , Christian Kanzow , Patrick Mehlitz

Consider the one-parameter generalizations of the logarithmic and exponential functions which are obtained from the integration of non-symmetrical hyperboles. These generalizations coincide to the one obtained in the context of…

General Finance · Quantitative Finance 2009-10-20 Alexandre Souto Martinez , Rodrigo Silva Gonzalez , Cesar Augusto Sangaletti Tercariol

We apply upper and lower compensated convex transforms, which are `tight' one-sided approximations of a given function, to the extraction of fine geometric singularities from semiconvex/semiconcave functions and DC-functions in…

Optimization and Control · Mathematics 2016-10-06 Kewei Zhang , Elaine Crooks , Antonio Orlando

We prove maximum and comparison principles for fractional discrete derivatives in the integers. Regularity results when the space is a mesh of length $h$, and approximation theorems to the continuous fractional derivatives are shown. When…

Analysis of PDEs · Mathematics 2016-05-24 Luciano Abadías , Marta de León-Contreras , José L. Torrea

The proximal gradient method is a standard approach for solving composite minimization problems in which the objective function is the sum of a continuously differentiable function and a lower semicontinuous, extended-valued function. The…

Optimization and Control · Mathematics 2025-05-02 Xiaoxi Jia , Kai Wang

A fast approximation to the Boys functions (related to the lower incomplete gamma function of half-integer parameter) by a single closed-form analytical expression for all argument values have been developed and tested. Besides the…

Numerical Analysis · Mathematics 2025-07-09 Dimitri N. Laikov

This paper studies the approximation of generalized ridge functions, namely of functions which are constant along some submanifolds of $\mathbb{R}^N$. We introduce the notion of linear-sleeve functions, whose function values only depend on…

Numerical Analysis · Mathematics 2017-01-26 Sandra Keiper

We propose some general growth conditions on the function $% f=f\left( x,\xi \right) $, including the so-called natural growth, or polynomial, or $p,q-$growth conditions, or even exponential growth, in order to obtain that any local…

Analysis of PDEs · Mathematics 2024-11-01 Paolo Marcellini , Antonella Nastasi , Cintia Pacchiano Camacho

In this paper, we describe an algorithm for approximating functions of the form $f(x)=\int_{a}^{b} x^{\mu} \sigma(\mu) \, d \mu$ over $[0,1]$, where $\sigma(\mu)$ is some signed Radon measure, or, more generally, of the form $f(x) =…

Numerical Analysis · Mathematics 2024-12-10 Mohan Zhao , Kirill Serkh

In this paper, using the concept of $A$-statistical convergence which is a regular (non-matrix) summability method, we obtain a general Korovkin type approximation theorem which concerns the problem of approximating a function $f$ by means…

Classical Analysis and ODEs · Mathematics 2007-05-23 Esra Erkus , Oktay Duman

This work revolves around the rigorous asymptotic analysis of models in nonlocal hyperelasticity. The corresponding variational problems involve integral functionals depending on nonlocal gradients with a finite interaction range $\delta$,…

Analysis of PDEs · Mathematics 2024-04-30 Javier Cueto , Carolin Kreisbeck , Hidde Schönberger

We consider the gradient method with variable step size for minimizing functions that are definable in o-minimal structures on the real field and differentiable with locally Lipschitz gradients. We prove that global convergence holds if…

Optimization and Control · Mathematics 2024-12-02 Cédric Josz

This paper is concerned with the $\Gamma$-limits of Ambrosio-Tortorelli-type functionals, for maps $u$ defined on an open bounded set $\Omega\subset\mathbb R^n$ and taking values in the unit circle $\mathbb S^1\subset\mathbb R^2$. Depending…

Analysis of PDEs · Mathematics 2025-05-14 Giovanni Bellettini , Roberta Marziani , Riccardo Scala

Let $G$ be a connected reductive group over a $p$-adic field $F$ of characteristic 0 and let $M$ be an $F$-Levi subgroup of $G.$ Given a discrete series representation $\sigma$ of $M(F),$ we prove that there exists a locally constant and…

Representation Theory · Mathematics 2018-06-29 Kwangho Choiy

A generalized conditional gradient method for minimizing the sum of two convex functions, one of them differentiable, is presented. This iterative method relies on two main ingredients: First, the minimization of a partially linearized…

Optimization and Control · Mathematics 2021-10-01 Karl Kunisch , Daniel Walter
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