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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

We develop fixed-point algorithms for the approximation of structured matrices with rank penalties. In particular we use these fixed-point algorithms for making approximations by sums of exponentials, or frequency estimation. For the basic…

Numerical Analysis · Mathematics 2016-01-07 Fredrik Andersson , Marcus Carlsson

We develop an estimator-based stochastic fixed-point framework for approximately computing the 2-Wasserstein barycenter of continuous, non-parametric probability measures. Notably, we provide the first rigorous convergence analysis for…

Optimization and Control · Mathematics 2026-04-17 Zeyi Chen , Ariel Neufeld , Qikun Xiang

We revisit the problem of recovering a low-rank positive semidefinite matrix from rank-one projections using tools from optimal transport. More specifically, we show that a variational formulation of this problem is equivalent to computing…

Optimization and Control · Mathematics 2022-10-27 Tyler Maunu , Thibaut Le Gouic , Philippe Rigollet

Maximum likelihood iteration is one of the most commonly used reconstruction algorithms in quantum tomography. The main appeal of the method is that it is easy to implement and that it converges reliably to a physically meaningful density…

Quantum Physics · Physics 2025-08-21 Florian Oberender

We study the problem of estimating precision matrices in Gaussian distributions that are multivariate totally positive of order two ($\mathrm{MTP}_2$). The precision matrix in such a distribution is an M-matrix. This problem can be…

Machine Learning · Computer Science 2023-10-24 Jian-Feng Cai , José Vinícius de M. Cardoso , Daniel P. Palomar , Jiaxi Ying

We introduce a fixed point iteration process built on optimization of a linear function over a compact domain. We prove the process always converges to a fixed point and explore the set of fixed points in various convex sets. In particular,…

Optimization and Control · Mathematics 2021-03-18 Pedro Felzenszwalb , Caroline Klivans , Alice Paul

Let $\mathcal{P}_{2,ac}$ be the set of Borel probabilities on $\mathbb{R}^d$ with finite second moment and absolutely continuous with respect to Lebesgue measure. We consider the problem of finding the barycenter (or Fr\'echet mean) of a…

Computation · Statistics 2016-04-25 Pedro C. Álvarez-Esteban , E. del Barrio , J. A. Cuesta-Albertos , C. Matrán

In this paper we analyse convergence of projected fixed-point iteration on a Riemannian manifold of matrices with fixed rank. As a retraction method we use `projector splitting scheme'. We prove that the projector splitting scheme converges…

Numerical Analysis · Mathematics 2016-04-08 Denis Kolesnikov , Ivan Oseledets

Computing the Wasserstein barycenter of a set of probability measures under the optimal transport metric can quickly become prohibitive for traditional second-order algorithms, such as interior-point methods, as the support size of the…

Optimization and Control · Mathematics 2020-01-22 Dongdong Ge , Haoyue Wang , Zikai Xiong , Yinyu Ye

In this paper, we introduce and study a new extragradient iterative process for finding a common element of the set of fixed points of an infinite family of nonexpansive mappings and the set of solutions of a variational inequality for an…

Functional Analysis · Mathematics 2014-05-22 Ibrahim Karahan , Murat Ozdemir

In this brief note, it is shown that the Bures-Wasserstein (BW) metric on the space positive definite matrices lends itself to convex optimization. In other words, the computation of the BW metric can be posed as a convex optimization…

Optimization and Control · Mathematics 2023-03-08 Shravan Mohan

Solving linear systems is a ubiquitous task in science and engineering. Because directly inverting a large-scale linear system can be computationally expensive, iterative algorithms are often used to numerically find the inverse. To…

Numerical Analysis · Mathematics 2021-07-20 Zheyuan Zhu , Andrew B. Klein , Guifang Li , Shuo Pang

In [C.W. Gear, T.J. Kaper, I.G. Kevrekidis, and A. Zagaris, Projecting to a Slow Manifold: Singularly Perturbed Systems and Legacy Codes, SIAM J. Appl. Dyn. Syst. 4 (2005) 711-732], we developed a class of iterative algorithms within the…

Dynamical Systems · Mathematics 2010-09-17 A. Zagaris , C. W. Gear , T. J. Kaper , I. G. Kevrekidis

This paper deals with a modifed iterative projection method for approximating a solution of hierarchical fixed point problems for nearly nonexpansive mappings. Some strong convergence theorems for the proposed method are presented under…

Functional Analysis · Mathematics 2014-03-17 Ibrahim Karahan , Murat Ozdemir

In computational inverse problems, it is common that a detailed and accurate forward model is approximated by a computationally less challenging substitute. The model reduction may be necessary to meet constraints in computing time when…

Methodology · Statistics 2018-02-14 Daniela Calvetti , Matthew M. Dunlop , Erkki Somersalo , Andrew M. Stuart

The Weber problem consists of finding a point in $\mathbbm{R}^n$ that minimizes the weighted sum of distances from $m$ points in $\mathbbm{R}^n$ that are not collinear. An application that motivated this problem is the optimal location of…

Optimization and Control · Mathematics 2015-03-20 Germán A. Torres

This paper deals with a modified iterative projection method for approximating a solution of the hierarchical fixed point problem for a sequene of nearly nonexpansive mappings with respect to a nonexpansive mapping. It is shown that under…

Functional Analysis · Mathematics 2014-03-14 Ibrahim Karahan , Murat Ozdemir

We introduce and investigate an iterative scheme for approximating common fixed point of a family of Bregman relatively-nonexpansive mappings in real reflexive Banach spaces. We prove strong convergence theorem of the sequence generated by…

Functional Analysis · Mathematics 2017-07-27 Oladipo Abiodun Timoye , Enyinnaya Ekuma-Okereke

Iterative phase retrieval algorithms typically employ projections onto constraint subspaces to recover the unknown phases in the Fourier transform of an image, or, in the case of x-ray crystallography, the electron density of a molecule.…

Numerical Analysis · Mathematics 2025-10-20 Veit Elser
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