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Feasibility problem aims to find a common point of two or more closed (convex) sets whose intersection is nonempty. In the literature, projection based algorithms are widely adopted to solve the problem, such as the method of alternating…

Optimization and Control · Mathematics 2025-04-16 Yuting Shen , Jingwei Liang

The study addresses the problem of precision in floating-point (FP) computations. A method for estimating the errors which affect intermediate and final results is proposed and a summary of many software simulations is discussed. The basic…

Numerical Analysis · Computer Science 2012-01-31 Glauco Masotti

Conventional finite-difference schemes for solving partial differential equations are based on approximating derivatives by finite-differences. In this work, an alternative theory is proposed which view finite-difference schemes as…

Numerical Analysis · Mathematics 2013-09-23 Siu A. Chin

Combining ideas from distributed algorithms and alternating automata, we introduce a new class of finite graph automata that recognize precisely the languages of finite graphs definable in monadic second-order logic. By restricting…

Formal Languages and Automata Theory · Computer Science 2018-07-03 Fabian Reiter

In this paper, we introduce a new problem called the split feasibility and fixed point equality problems (SFFPEP) and propose a new iterative algorithm for solving the problem (SFFPEP) for the class of quasi-nonexpansive mappings in Hilbert…

Functional Analysis · Mathematics 2016-10-10 L. B. Mohammed , A. Kılıçman

We implement four algorithms for solving linear Diophantine equations in the naturals: a lexicographic enumeration algorithm, a completion procedure, a graph-based algorithm, and the Slopes algorithm. As already known, the lexicographic…

Data Structures and Algorithms · Computer Science 2021-04-13 Valeriu Motroi , Stefan Ciobaca

Stable distribution is one of the attractive models that well describes fat-tail behaviors and scaling phenomena in various scientific fields. The approach based upon the method of moments yields a simple procedure for estimating stable law…

Methodology · Statistics 2021-06-24 Shinji Kakinaka , Ken Umeno

In this work, we deal with an iteration method for approximating a fixed point of a contraction mapping using the Mann's algorithm under functional random errors. We first show its almost complete convergence to the fixed point by mean of…

Probability · Mathematics 2017-01-24 Bahia Barache , Idir Arab , Abdelnasser Dahmani

In this paper, we are interested in the number of fixed points of functions $f:A^n\to A^n$ over a finite alphabet $A$ defined on a given signed digraph $D$. We first use techniques from network coding to derive some lower bounds on the…

Discrete Mathematics · Computer Science 2014-09-23 Maximilien Gadouleau , Adrien Richard , Søren Riis

In this paper, we propose a new general and stable fixed-point approach to compute the resolvents of the composition of a set-valued maximal monotone operator with a linear bounded mapping. Weak, strong and linear convergence of the…

Optimization and Control · Mathematics 2025-02-05 Samir Adly , Ba Khiet Le

This paper analyzes the problem of assigning weights to edges incrementally in a dynamic complete bipartite graph consisting of producer and consumer nodes. The objective is to minimize the overall cost while satisfying certain constraints.…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-05-03 Ankur Sahai

In this paper, we introduce a new type of Darbo's fixed point theorem by using concept of function sequences with shifting distance property. Afterward, we investigate existence of fixed point under this the theorem. Also we are going to…

Functional Analysis · Mathematics 2021-02-23 Vatan Karakaya , Necip Şimşek , Derya Sekman

The Langevin algorithms are frequently used to sample the posterior distributions in Bayesian inference. In many practical problems, however, the posterior distributions often consist of non-differentiable components, posing challenges for…

Numerical Analysis · Mathematics 2023-04-11 Ziruo Cai , Jinglai Li , Xiaoqun Zhang

Two-time-scale stochastic approximation is a popular iterative method for finding the solution of a system of two equations. Such methods have found broad applications in many areas, especially in machine learning and reinforcement…

Optimization and Control · Mathematics 2019-12-24 Thinh T. Doan , Justin Romberg

Part I of this work [2] developed the exact diffusion algorithm to remove the bias that is characteristic of distributed solutions for deterministic optimization problems. The algorithm was shown to be applicable to a larger set of…

Optimization and Control · Mathematics 2017-12-27 Kun Yuan , Bicheng Ying , Xiaochuan Zhao , Ali H. Sayed

In classic distributed graph problems, each instance on a graph specifies a space of feasible solutions (e.g. all proper ($\Delta+1$)-list-colorings of the graph), and the task of distributed algorithm is to construct a feasible solution…

Data Structures and Algorithms · Computer Science 2018-02-20 Weiming Feng , Yitong Yin

We present a new algorithm for finding an $\epsilon$-approximate fixed point of an $\ell_\infty$-contracting function $f : [0, 1]^d \rightarrow [0, 1]^d$. Our algorithm is based on the query-efficient algorithm by Chen, Li, and Yannakakis…

Data Structures and Algorithms · Computer Science 2026-04-02 Andrei Feodorov , Sebastian Haslebacher

This work considers the distributed computation of the one-to-one vertex correspondences between two undirected and connected graphs, which is called \textit{graph matching}, over multi-agent networks. Given two \textit{isomorphic} and…

Optimization and Control · Mathematics 2020-02-21 Quoc Van Tran , Zhiyong Sun , Brian D. O. Anderson , Hyo-Sung Ahn

This work studies distributed algorithms for locally optimal load-balancing: We are given a graph of maximum degree $\Delta$, and each node has up to $L$ units of load. The task is to distribute the load more evenly so that the loads of…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-02-17 Laurent Feuilloley , Juho Hirvonen , Jukka Suomela

Iterative Proportional Fitting (IPF), combined with EM, is commonly used as an algorithm for likelihood maximization in undirected graphical models. In this paper, we present two iterative algorithms that generalize upon IPF. The first one…

Machine Learning · Computer Science 2013-01-07 Wim Wiegerinck , Tom Heskes
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