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Matrix Factorization plays an important role in machine learning such as Non-negative Matrix Factorization, Principal Component Analysis, Dictionary Learning, etc. However, most of the studies aim to minimize the loss by measuring the…

Machine Learning · Computer Science 2021-11-30 Kai Liu

Certain triangle inequalities involving the circumradius, inradius, and side lengths of a triangle are generalized to spherical and hyperbolic geometry. Examples include strengthenings of Euler's inequality, $R\geq2r$. An extension of…

History and Overview · Mathematics 2018-05-30 Karina Cho , Jacob Naranjo

Motivated by a question of R.\ Nandakumar, we show that the Euclidean plane can be dissected into mutually incongruent convex quadrangles of the same area and the same perimeter. As a byproduct we obtain vertex-to-vertex dissections of the…

Metric Geometry · Mathematics 2020-04-03 Dirk Frettlöh , Christian Richter

In his seminal paper on triangle centers, Clark Kimberling made a number of conjectures concerning the distances between triangle centers. For example, if $D(i; j)$ denotes the distance between triangle centers $X_i$ and $X_j$ , Kimberling…

History and Overview · Mathematics 2023-09-26 Stanley Rabinowitz

We study quantitative isoperimetric inequalities for two different perimeter-type functionals. We first consider classical capillarity functionals, which measure the perimeter of sets in a Euclidean half-space, assigning a constant weight…

Differential Geometry · Mathematics 2025-07-22 Davide Carazzato , Giulio Pascale , Marco Pozzetta

This paper provides rates of convergence for empirical (generalised) barycenters on compact geodesic metric spaces under general conditions using empirical processes techniques. Our main assumption is termed a variance inequality and…

Statistics Theory · Mathematics 2019-06-03 Adil Ahidar-Coutrix , Thibaut Le Gouic , Quentin Paris

In this article, we establish weighted strong and weak type inequalities for non-commutative square functions that naturally arise in the analysis of differences between ball averages and martingale sequences within the framework of group…

Functional Analysis · Mathematics 2026-01-05 Panchugopal Bikram , Diptesh Saha

S-metric and b-metric spaces are metrizable, but it is still quite impossible to get an explicit form of the concerned metric function. To overcome this, the notion of $\phi$-metric is developed by making a suitable modification in triangle…

General Mathematics · Mathematics 2023-08-21 Abhishikta Das , Anirban Kundu , T. Bag

Metric spaces $(X, d)$ are ubiquitous objects in mathematics and computer science that allow for capturing (pairwise) distance relationships $d(x, y)$ between points $x, y \in X$. Because of this, it is natural to ask what useful…

Computational Geometry · Computer Science 2023-08-10 Willow Barkan-Vered , Huck Bennett , Amir Nayyeri

Certain many-particle Hardy inequalities are derived in a simple and systematic way using the so-called ground state representation for the Laplacian on a subdomain of $\mathbb{R}^n$. This includes geometric extensions of the standard Hardy…

Mathematical Physics · Physics 2015-04-14 Douglas Lundholm

In this paper we propose a general algorithmic framework for first-order methods in optimization in a broad sense, including minimization problems, saddle-point problems and variational inequalities. This framework allows to obtain many…

Multiview varieties are mathematical models for the set of image feature correspondences that can be produced by a given camera arrangement. They possess an invariant known as their Euclidean distance (ED) degree, which measures the…

Algebraic Geometry · Mathematics 2026-03-10 Bella Finkel , Jose Israel Rodriguez

We study the problem of recovering a globally consistent Euclidean embedding of data, given only a local distance graph and propose a method that optimally represents these distances. The method operates solely on a neighborhood graph…

Machine Learning · Computer Science 2026-05-20 Dimitris Arabadjis

Using isometric embedding of metric trees into Banach spaces, this paper will investigate barycenters, type and cotype, and various measures of compactness of metric trees. A metric tree ($T$, $d$) is a metric space such that between any…

Metric Geometry · Mathematics 2010-07-15 Asuman Guven Aksoy , Timur Oikhberg

To improve our understanding of connected systems, different tools derived from statistics, signal processing, information theory and statistical physics have been developed in the last decade. Here, we will focus on the graph comparison…

Physics and Society · Physics 2018-04-23 Johann H. Martínez , Mario Chavez

A new framework based on Boltzmann equation which is genuinely multidimensional and mesh-less is developed for solving Euler's equations. The idea is to use the method of moment of Boltzmann equation to operate in multidimensions using…

Computational Physics · Physics 2015-10-02 Praveer Tiwari , S. V. Raghurama Rao

Euler's inequality is a well known inequality relating the inradius and circumradius of a triangle. In Euclidean geometry, this inequality takes the form $R \geq 2r$ where $R$ is the circumradius and $r$ is the inradius. In spherical…

Metric Geometry · Mathematics 2025-11-19 Ren Guo , Estonia Black , Caleb Smith

We extend the generic Bell inequalities suggested by Son, Lee, and Kim [Phys. Rev. Lett. 96, 060406 (2006)] to incorporate multiple observables for tripartite systems and introduce a geometric methodology for calculating classical upper…

Quantum Physics · Physics 2025-10-08 Junghee Ryu , Jinhyoung Lee , Hoon Ryu

The goal of this paper is to provide computational tools able to find a solution of a system of polynomial inequalities. The set of inequalities is reformulated as a system of polynomial equations. Three different methods, two of which…

Dynamical Systems · Mathematics 2016-03-04 Laura Menini , Corrado Possieri , Antonio Tornambè

Recent literature has shown that symbolic data, such as text and graphs, is often better represented by points on a curved manifold, rather than in Euclidean space. However, geometrical operations on manifolds are generally more complicated…

Machine Learning · Computer Science 2019-02-06 Max Aalto , Nakul Verma