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We consider approximation of diameter of a set $S$ of $n$ points in dimension $m$. E$\tilde{g}$ecio$\tilde{g}$lu and Kalantari \cite{kal} have shown that given any $p \in S$, by computing its farthest in $S$, say $q$, and in turn the…

Computational Geometry · Computer Science 2014-10-09 Sharareh Alipour , Bahman Kalantari , Hamid Homapour

This paper presents a novel boundary-optimized fast Fourier extension algorithm for efficient approximation of non-periodic functions. The proposed methodology constructs periodic extensions through strategic utilization of boundary…

Numerical Analysis · Mathematics 2025-08-27 Z. Y. Zhao , Y. F Wang , A. G. Yagola

This paper focuses on regularisation methods using models up to the third order to search for up to second-order critical points of a finite-sum minimisation problem. The variant presented belongs to the framework of [3]: it employs random…

Numerical Analysis · Mathematics 2021-04-05 Stefania Bellavia , Gianmarco Gurioli , Benedetta Morini , Philippe L. Toint

This paper presents a new approach in application of the Fourier transform to the complex error function resulting in an efficient rational approximation. Specifically, the computational test shows that with only $17$ summation terms the…

General Mathematics · Mathematics 2016-02-02 S. M. Abrarov , B. M. Quine

The proximal gradient algorithm has been popularly used for convex optimization. Recently, it has also been extended for nonconvex problems, and the current state-of-the-art is the nonmonotone accelerated proximal gradient algorithm.…

Optimization and Control · Mathematics 2017-05-24 Quanming Yao , James T. Kwok , Fei Gao , Wei Chen , Tie-Yan Liu

Point sets matching method is very important in computer vision, feature extraction, fingerprint matching, motion estimation and so on. This paper proposes a robust point sets matching method. We present an iterative algorithm that is…

Computer Vision and Pattern Recognition · Computer Science 2014-11-05 Xiao Liu , Congying Han , Tiande Guo

Our work presents a new iterative scheme to approximate the fixed points of nonexpansive mapping. The proposed algorithm is constructed to enhance convergence efficiency while preserving theoretical robustness. Under appropriate assumptions…

Functional Analysis · Mathematics 2026-01-12 Nida Izhar Mallick , Izhar Uddin

The two currently fastest general-purpose integer factorization algorithms are the Quadratic Sieve and the Number Field Sieve. Both techniques are used to find so-called smooth values of certain polynomials, i.e., values that factor…

Number Theory · Mathematics 2024-05-01 Markus Hittmeir

In this paper, a distributed stochastic approximation algorithm is studied. Applications of such algorithms include decentralized estimation, optimization, control or computing. The algorithm consists in two steps: a local step, where each…

Optimization and Control · Mathematics 2013-12-03 Pascal Bianchi , Gersende Fort , Walid Hachem

Matrix factorization (MF) is a widely used collaborative filtering (CF) algorithm for recommendation systems (RSs), due to its high prediction accuracy, great flexibility and high efficiency in big data processing. However, with the…

Information Retrieval · Computer Science 2026-03-26 Yining Wu , Shengyu Duan , Gaole Sai , Chenhong Cao , Guobing Zou

In many applications of tomography, the acquired projections are either limited in number or contain a significant amount of noise. In these cases, standard reconstruction methods tend to produce artifacts that can make further analysis…

Numerical Analysis · Mathematics 2016-04-11 D. M. Pelt , K. J. Batenburg

This paper deals with speeding up the convergence of a class of two-step iterative methods for solving linear systems of equations. To implement the acceleration technique, the residual norm associated with computed approximations for each…

Numerical Analysis · Mathematics 2024-04-24 Fatemeh P. A. Beik , Michele Benzi , Mehdi Najafi-Kalyani

We give an algorithm for computing approximate PSD factorizations of nonnegative matrices. The running time of the algorithm is polynomial in the dimensions of the input matrix, but exponential in the PSD rank and the approximation error.…

Data Structures and Algorithms · Computer Science 2016-02-25 Amitabh Basu , Michael Dinitz , Xin Li

A simple greedy refinement procedure for the generation of data-adapted triangulations is proposed and studied. Given a function of two variables, the algorithm produces a hierarchy of triangulations and piecewise polynomial approximations…

Numerical Analysis · Mathematics 2015-03-17 Albert Cohen , Nira Dyn , Frédéric Hecht , Jean-Marie Mirebeau

Random Reshuffling (RR), also known as Stochastic Gradient Descent (SGD) without replacement, is a popular and theoretically grounded method for finite-sum minimization. We propose two new algorithms: Proximal and Federated Random…

Machine Learning · Computer Science 2021-02-15 Konstantin Mishchenko , Ahmed Khaled , Peter Richtárik

We present a combination of two algorithms that accurately calculate multiple roots of general polynomials. Algorithm I transforms the singular root-finding into a regular nonlinear least squares problem on a pejorative manifold, and…

Numerical Analysis · Mathematics 2023-01-20 Zhonggang Zeng

The algorithms of Pan (1995) and(2002) approximate the roots of a complex univariate polynomial in nearly optimal arithmetic and Boolean time but require precision of computing that exceeds the degree of the polynomial. This causes…

Symbolic Computation · Computer Science 2016-11-10 Victor Y. Pan , Elias P. Tsigaridas , Vitaly Zaderman , Liang Zhao

Recently, a new polynomial basis over binary extension fields was proposed such that the fast Fourier transform (FFT) over such fields can be computed in the complexity of order $\mathcal{O}(n\lg(n))$, where $n$ is the number of points…

Information Theory · Computer Science 2016-08-16 Sian-Jheng Lin , Tareq Y. Al-Naffouri , Yunghsiang S. Han

The goal of this paper is to study approaches to bridge the gap between first-order and second-order type methods for composite convex programs. Our key observations are: i) Many well-known operator splitting methods, such as…

Optimization and Control · Mathematics 2016-09-27 Xiantao Xiao , Yongfeng Li , Zaiwen Wen , Liwei Zhang

We analyze the convergence rate of the random reshuffling (RR) method, which is a randomized first-order incremental algorithm for minimizing a finite sum of convex component functions. RR proceeds in cycles, picking a uniformly random…

Optimization and Control · Mathematics 2022-02-09 Mert Gürbüzbalaban , Asuman Ozdaglar , Pablo Parrilo
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