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We consider a variation of the classical proximal-gradient algorithm for the iterative minimization of a cost function consisting of a sum of two terms, one smooth and the other prox-simple, and whose relative weight is determined by a…

Optimization and Control · Mathematics 2024-10-04 Jean-Baptiste Fest , Tommi Heikkilä , Ignace Loris , Ségolène Martin , Luca Ratti , Simone Rebegoldi , Gesa Sarnighausen

We study nominal anti-unification, which is concerned with computing least general generalizations for given terms-in-context. In general, the problem does not have a least general solution, but if the set of atoms permitted in…

Logic in Computer Science · Computer Science 2025-05-01 Alexander Baumgartner , Temur Kutsia , Jordi Levy , Mateu Villaret

We reinterpret multiplicative noise in neural networks as auxiliary random variables that augment the approximate posterior in a variational setting for Bayesian neural networks. We show that through this interpretation it is both efficient…

Machine Learning · Statistics 2017-06-14 Christos Louizos , Max Welling

We give estimates for the convolution product of an arbitrary number of endlessly continuable functions. This allows us to deal with nonlinear operations for the corresponding resurgent series, e.g. substitution into a convergent power…

Dynamical Systems · Mathematics 2016-09-07 Shingo Kamimoto , David Sauzin

Function approximation and recovery via some sampled data have long been studied in a wide array of applied mathematics and statistics fields. Analytic tools, such as the Poincar\'e inequality, have been handy for estimating the…

Numerical Analysis · Mathematics 2020-07-16 Yifan Chen , Thomas Y. Hou

This paper presents convergence acceleration, a method for computing efficiently the limit of numerical sequences as a typical application of streams and higher-order functions.

Numerical Analysis · Computer Science 2014-03-04 Pierre Lescanne

Given a finite number of samples of a continuous set-valued function F, mapping an interval to compact subsets of the real line, we develop good approximations of F, which can be computed efficiently.

Numerical Analysis · Mathematics 2022-09-01 Qusay Muzaffar , Nira Dyn , David Levin

In this paper upper bounds are given for the successive differences $A_{n+1}-A_{n}$ and B$_{n}-B_{n-1}$ where $A_{n}=1/(n-1) \tsum_{r=1}^{n-1}f(r/n)$, $B_{n}=1/(n+1) \tsum_{r=0}^{n}f(r/n)$ and $f$ is superquadratic function. We obtain…

Numerical Analysis · Mathematics 2011-10-25 Shoshana Abramovich , Josipa Barić , Marko Matić , Josip Pečarić

We prove an intermediate value theorem of an arithmetical flavor, involving the consecutive averages of sequences with terms in a given finite set A. For every such set we completely characterize the numbers x ("intermediate values") with…

General Mathematics · Mathematics 2007-05-23 Mihai Caragiu , Laurence D. Robinson

We derive normal approximation results for a class of stabilizing functionals of binomial or Poisson point process, that are not necessarily expressible as sums of certain score functions. Our approach is based on a flexible notion of the…

Probability · Mathematics 2022-10-20 Zhaoyang Shi , Krishnakumar Balasubramanian , Wolfgang Polonik

We derive necessary and sufficient conditions for a continuous bounded function $f: R\to C$ to be a characteristic function of a probability measure. The Cauchy transform $K_f$ of $f$ is used as analytic continuation of $f$ to the upper and…

Classical Analysis and ODEs · Mathematics 2020-09-11 Saulius Norvidas

Standardness is a popular assumption in the literature on set estimation. It also appears in statistical approaches to topological data analysis, where it is common to assume that the data were sampled from a probability measure that…

Statistics Theory · Mathematics 2025-02-27 Alejandro Cholaquidis , Leonardo Moreno , Beatriz Pateiro-López

We introduce the notion of an approximation system as a generalization of Taylor approximation, and we give some first examples. Next we develop the general theory, including error bounds and a sufficient criterion for convergence. More…

Classical Analysis and ODEs · Mathematics 2017-10-20 Victor A. Pessers , Tom H. Koornwinder

Discrimination in machine learning often arises along multiple dimensions (a.k.a. protected attributes); it is then desirable to ensure \emph{intersectional fairness} -- i.e., that no subgroup is discriminated against. It is known that…

Machine Learning · Statistics 2023-06-27 Mathieu Molina , Patrick Loiseau

Typical performance of approximation algorithms is studied for randomized minimum vertex cover problems. A wide class of random graph ensembles characterized by an arbitrary degree distribution is discussed with some theoretical frameworks.…

Disordered Systems and Neural Networks · Physics 2016-11-10 Satoshi Takabe , Koji Hukushima

The purpose of this paper is twofold. First, the definition of new statistical convergence with Fibonacci sequence is given and some fundamental properties of statistical convergence are examined. Second, approximation theory worked as a…

Functional Analysis · Mathematics 2016-07-11 Murat Kirisci , Ali Karaisa

Motivated by conforming finite element methods for elliptic problems of second order, we analyze the approximation of the gradient of a target function by continuous piecewise polynomial functions over a simplicial mesh. The main result is…

Numerical Analysis · Mathematics 2018-03-07 Andreas Veeser

Let $\A$ be the operator which assigns to each $m \times n$ matrix-valued function on the unit circle with entries in $H^\infty + C$ its unique superoptimal approximant in the space of bounded analytic $m \times n$ matrix-valued functions…

Functional Analysis · Mathematics 2016-09-06 Vladimir V. Peller , Nicholas J. Young

In this paper, we hope to bring closer graph theory and consensus algorithms. Firstly, we give a brief introduction to graph theory by listing a concise definition. Then we analyze and visualize some commonly used graphs. Secondly, we…

Discrete Mathematics · Computer Science 2021-01-27 Shen Zheng

The aim of this paper is to study the characteristics of a general method to produce a new approximation sequence from a given one, by using suitable convex combinations.

Functional Analysis · Mathematics 2007-05-23 Lorenzo D'Ambrosio , Elisabetta Mangino
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