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Related papers: Constrained Fermat-Torricelli-Weber Problem in rea…

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We solve the problem of best approximation by Parseval frames to an arbitrary frame in a subspace of an infinite dimensional Hilbert space. We explicitly describe all the solutions and we give a criterion for uniqueness. This best…

Functional Analysis · Mathematics 2017-11-27 Eduardo Chiumiento

Convex feasibility problems require to find a point in the intersection of a finite family of convex sets. We propose to solve such problems by performing set-enlargements and applying a new kind of projection operators called valiant…

Optimization and Control · Mathematics 2017-09-19 Yair Censor , Rafiq Mansour

We investigate the Fermat-Torricelli problem in d-dimensional real normed spaces or Minkowski spaces, mainly for d=2. Our approach is to study the Fermat-Torricelli locus in a geometric way. We present many new results, as well as give an…

Optimization and Control · Mathematics 2007-07-18 Horst Martini , Konrad J Swanepoel , Gunter Weiss

This work investigates minimal parametric networks in hyperspaces of closed subsets of metric spaces endowed with the Hausdorff distance. It is shown that the problems of finding such networks are nontrivial only within finiteness classes,…

Metric Geometry · Mathematics 2026-05-11 Arsen Galstyan

The convex body chasing problem, introduced by Friedman and Linial, is a competitive analysis problem on any normed vector space. In convex body chasing, for each timestep $t\in\mathbb N$, a convex body $K_t\subseteq \mathbb R^d$ is given…

Data Structures and Algorithms · Computer Science 2021-08-16 Sébastien Bubeck , Bo'az Klartag , Yin Tat Lee , Yuanzhi Li , Mark Sellke

Riemannian optimization uses local methods to solve optimization problems whose constraint set is a smooth manifold. A linear step along some descent direction usually leaves the constraints, and hence retraction maps are used to…

Statistics Theory · Mathematics 2023-01-19 Alexander Heaton , Matthias Himmelmann

The Wasserstein distance received a lot of attention recently in the community of machine learning, especially for its principled way of comparing distributions. It has found numerous applications in several hard problems, such as domain…

Machine Learning · Statistics 2017-10-23 Nicolas Courty , Rémi Flamary , Mélanie Ducoffe

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

We consider a constrained minimax single facility location problem on the plane with rectilinear distance. The feasible set of location points is restricted to rectangles with sides oriented at a 45 degrees angle to the axes of Cartesian…

Optimization and Control · Mathematics 2012-12-27 Nikolai Krivulin

This paper introduces and solves the Generalized Heron-Waist Problem (GHWP), that integrates the classical Heron problem of optimal hub location and the waist problem of minimal-perimeter configuration. The GHWP seeks an optimal closed…

Optimization and Control · Mathematics 2026-03-03 Manohar Choudhary , Triloki Nath , Ram K. Pandey

The Nelder-Mead algorithm, a longstanding direct search method for unconstrained optimization published in 1965, is designed to minimize a scalar-valued function f of n real variables using only function values, without any derivative…

Optimization and Control · Mathematics 2017-04-03 Jeffrey C. Lagarias , Bjorn Poonen , Margaret H. Wright

We provide new complexity information for the convergence of the Hybrid Steepest Descent Method for solving the Variational Inequality Problem for a strict contraction on Hilbert space over a closed convex set C given either as the fixed…

Logic · Mathematics 2016-10-04 Daniel Körnlein

Over an algebraically closed field, the $\textit{double point interpolation}$ problem asks for the vector space dimension of the projective hypersurfaces of degree $d$ singular at a given set of points. After being open for 90 years, a…

Commutative Algebra · Mathematics 2024-08-13 Shahriyar Roshan-Zamir

We present a new approach to approximate nearest-neighbor queries in fixed dimension under a variety of non-Euclidean distances. We are given a set $S$ of $n$ points in $\mathbb{R}^d$, an approximation parameter $\varepsilon > 0$, and a…

Computational Geometry · Computer Science 2023-06-28 Ahmed Abdelkader , Sunil Arya , Guilherme D. da Fonseca , David M. Mount

The complexity of Philip Wolfe's method for the minimum Euclidean-norm point problem over a convex polytope has remained unknown since he proposed the method in 1974. The method is important because it is used as a subroutine for one of the…

Optimization and Control · Mathematics 2017-11-07 Jesus De Loera , Jamie Haddock , Luis Rademacher

Under investigation is the problem of finding the best approximation of a function in a Hilbert space subject to convex constraints and prescribed nonlinear transformations. We show that in many instances these prescriptions can be…

Functional Analysis · Mathematics 2021-06-17 Patrick L. Combettes , Zev C. Woodstock

This paper considers a networked system with a finite number of users and supposes that each user tries to minimize its own private objective function over its own private constraint set. It is assumed that each user's constraint set can be…

Optimization and Control · Mathematics 2015-10-22 Hideaki Iiduka

In this work we solve, for given bounded operators $B,C$ and Hilbert-Schmidt operator $M$ acting on potentially infinite-dimensional separable Hilbert spaces, the reduced rank approximation problem, $\min\{\lVert M-BXC\rVert_{L_2}:\…

Functional Analysis · Mathematics 2026-05-27 Giuseppe Carere , Han Cheng Lie

We consider an optimization problem in a convex space $E$ with an affine objective function, subject to $J$ constraints in the forms of inequalities on some other affine functions, where $J$ is a given nonnegative integer. Under suitable…

Optimization and Control · Mathematics 2023-05-11 Alexey Piunovskiy , Yi Zhang

Classifying points in high dimensional spaces is a fundamental geometric problem in machine learning. In this paper, we address classifying points in the $d$-dimensional Hilbert polygonal metric. The Hilbert metric is a generalization of…

Computational Geometry · Computer Science 2026-01-21 Aditya Acharya , Auguste H. Gezalyan , David M. Mount