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This expository essay discusses a finite dimensional approach to dilation theory. How much of dilation theory can be worked out within the realm of linear algebra? It turns out that some interesting and simple results can be obtained. These…

Functional Analysis · Mathematics 2014-12-23 Eliahu Levy , Orr Shalit

There has been a lot of interest in sufficient dimension reduction (SDR) methodologies as well as nonlinear extensions in the statistics literature. In this note, we use classical results regarding metric spaces and positive definite…

Methodology · Statistics 2020-10-29 Youngjoo Cho , Debashis Ghosh

High dimensional data can have a surprising property: pairs of data points may be easily separated from each other, or even from arbitrary subsets, with high probability using just simple linear classifiers. However, this is more of a rule…

Machine Learning · Computer Science 2023-11-15 Oliver J. Sutton , Qinghua Zhou , Alexander N. Gorban , Ivan Y. Tyukin

Basic algebraic and combinatorial properties of finite vector spaces in which individual vectors are allowed to have multiplicities larger than $ 1 $ are derived. An application in coding theory is illustrated by showing that multispace…

Information Theory · Computer Science 2024-09-04 Mladen Kovačević

We first consider interval partitions whose complements are Lebesgue-null and introduce a complete metric that induces the same topology as the Hausdorff distance (between complements). This is done using correspondences between intervals.…

Probability · Mathematics 2021-01-29 Noah Forman , Soumik Pal , Douglas Rizzolo , Matthias Winkel

We define two notions of discrete dimension based on the Minkowski and Hausdorff dimensions in the continuous setting. After proving some basic results illustrating these definitions, we apply this machinery to the study of connections…

Combinatorics · Mathematics 2007-07-10 Alex Iosevich , Misha Rudnev , Ignacio Uriarte-Tuero

Linear complementarity problems provide a powerful framework to model nonsmooth phenomena in a variety of real-world applications. In dynamical control systems, they appear coupled to a linear input-output system in the form of linear…

Systems and Control · Electrical Eng. & Systems 2023-03-23 Felix Miranda-Villatoro , Fernando Castaños , Alessio Franci

Magnitude is a numerical invariant of metric spaces introduced by Leinster, motivated by considerations from category theory. This paper extends the original definition for finite spaces to compact spaces, in an equivalent but more natural…

Metric Geometry · Mathematics 2015-07-22 Mark W. Meckes

We give a systematic and thorough study of geometric notions and results connected to Minkowski's measure of symmetry and the extension of the well-known Minkowski functional to arbitrary, not necessarily symmetric convex bodies K on any…

Classical Analysis and ODEs · Mathematics 2007-05-23 Szilard Gy. Revesz

Symmetry groups allow to transform solutions of differential equations continuously into other solutions. This property can be used for the observability analysis of infinite-dimensional systems with input and output. In this contribution,…

Optimization and Control · Mathematics 2019-05-28 Bernd Kolar , Markus Schöberl

Functions with uniform level sets can represent orders, preference relations or other binary relations and thus turn out to be a tool for scalarization that can be used, e.g., in multicriteria optimization, decision theory, mathematical…

Optimization and Control · Mathematics 2016-08-11 Petra Weidner

We consider a fairly general class of natural non standard metric products and classify those amongst them, which yield a product of certain type (for instance an inner metric space) for all possible choices of factors of this type (inner…

Metric Geometry · Mathematics 2007-05-23 Andreas Bernig , Thomas Foertsch , Viktor Schroeder

Bender, Coley, Robbins and Rumsey posed the problem of counting the number of subspaces which have a given profile with respect to a linear endomorphism defined on a finite vector space. Several special cases of this problem have been…

Combinatorics · Mathematics 2026-05-26 Samrith Ram

Several machine learning models are defined for inputs of any size, such as graphs with different numbers of nodes and point clouds containing varying numbers of points. The universality properties of such any-dimensional models remain…

Machine Learning · Computer Science 2026-05-25 Shengtai Yao , Eitan Levin , Mateo Díaz

Supervised dimensionality reduction has emerged as an important theme in the last decade. Despite the plethora of models and formulations, there is a lack of a simple model which aims to project the set of patterns into a space defined by…

Machine Learning · Statistics 2016-10-28 Anthony O. Smith , Anand Rangarajan

As objects of study in functional analysis, Hilbert spaces stand out as special objects of study as do nuclear spaces in view of a rich geometrical structure they possess as Banach and Frechet spaces, respectively. On the other hand, there…

Functional Analysis · Mathematics 2013-10-29 M A Sofi

Model sets (also called cut and project sets) are generalizations of lattices, and multi-component model sets are generalizations of lattices with colourings. In this paper, we study self-similarities of multi-component model sets. The main…

Mathematical Physics · Physics 2007-05-23 Michael Baake , Robert V. Moody

We present several analogies between convex geometry and the theory of holomorphic line bundles on smooth projective varieties or K\"ahler manifolds. We study the relation between positive products and mixed volumes. We define and study a…

Algebraic Geometry · Mathematics 2023-06-22 Brian Lehmann , Jian Xiao

In this paper it is stressed that there is no {\em physical} reason for symmetries to be linear and that Lie group theory is therefore too restrictive. We illustrate this with some simple examples. Then we give a readable review on the…

High Energy Physics - Theory · Physics 2008-11-26 Jan de Boer , Frederique Harmsze , Tjark Tjin

Magnitude, obtained as a special case of Euler characteristic of enriched category, represents a sense of the size of metric spaces and is related to classical notions such as cardinality, dimension, and volume. While the studies have…

Machine Learning · Statistics 2025-09-16 Byungchang So