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Uniform cost-distance Steiner trees minimize the sum of the total length and weighted path lengths from a dedicated root to the other terminals. They are applied when the tree is intended for signal transmission, e.g. in chip design or…

Data Structures and Algorithms · Computer Science 2025-07-31 Josefine Foos , Stephan Held , Yannik Kyle Dustin Spitzley

The concept of $n$-distance was recently introduced to generalize the classical definition of distance to functions of $n$ arguments. In this paper we investigate this concept through a number of examples based on certain geometrical…

Metric Geometry · Mathematics 2023-02-22 Gergely Kiss , Jean-Luc Marichal

We consider the problem of describing the typical (possibly) non-linear code of minimum distance bounded from below over a large alphabet. We concentrate on block codes with the Hamming metric and on subspace codes with the injection…

Information Theory · Computer Science 2021-11-24 Anina Gruica , Alberto Ravagnani

This paper studies separating invariants: mappings on $D$ dimensional domains which are invariant to an appropriate group action, and which separate orbits. The motivation for this study comes from the usefulness of separating invariants in…

Machine Learning · Computer Science 2023-11-22 Nadav Dym , Steven J. Gortler

Maximum mean discrepancies (MMDs) like the kernel Stein discrepancy (KSD) have grown central to a wide range of applications, including hypothesis testing, sampler selection, distribution approximation, and variational inference. In each…

Machine Learning · Statistics 2025-03-26 Alessandro Barp , Carl-Johann Simon-Gabriel , Mark Girolami , Lester Mackey

The notion of unbiased orthogonal designs is introduced as a generalization among unbiased Hadamard matrices, unbiased weighing matrices and quasi-unbiased weighing matrices. We provide upper bounds and several constructions for mutually…

Combinatorics · Mathematics 2016-01-19 Hadi Kharaghani , Sho Suda

We propose a framework, named Aggregated Wasserstein, for computing a dissimilarity measure or distance between two Hidden Markov Models with state conditional distributions being Gaussian. For such HMMs, the marginal distribution at any…

Machine Learning · Computer Science 2016-08-08 Yukun Chen , Jianbo Ye , Jia Li

Let $n \in \mathbb{N}_{\geq 2}$. We prove that for every $k \geq 4$ there exist uniform but non-homogeneous Steiner bundles on $\mathbb{P}^n$ of $k$-type with disconnected splitting type, and we further investigate almost-uniform Steiner…

Representation Theory · Mathematics 2025-09-03 Daniel Bissinger

We introduce a uniform method of proof for the following results. For {\em each} of the following conditions, there are $2^{\aleph_0}$ families of Steiner systems, satisfying that condition: i) Theorem~2.2.4: (extending \cite{Chicoetal})…

Combinatorics · Mathematics 2022-01-28 John T. Baldwin

The Steiner distance of a graph, introduced by Chartrand, Oellermann, Tian and Zou in 1989, is a natural generalization of the concept of classical graph distance. For a connected graph $G$ of order at least $2$ and $S\subseteq V(G)$, the…

Combinatorics · Mathematics 2017-02-21 Zhao Wang , Yaping Mao , Hengzhe Li , Chengfu Ye

One of the most intriguing problems, in $q$-analogs of designs and codes, is the existence question of an infinite family of $q$-analog of Steiner systems (spreads not included) in general, and the existence question for the $q$-analog of…

Combinatorics · Mathematics 2017-02-07 Tuvi Etzion

A unitary design is a collection of unitary matrices that approximate the entire unitary group, much like a spherical design approximates the entire unit sphere. In this paper, we use irreducible representations of the unitary group to find…

Combinatorics · Mathematics 2009-08-31 Aidan Roy , A. J. Scott

In this paper, we consider the existence of group divisible designs (GDDs) with block size $4$ and group sizes $4$ and $7$. We show that there exists a 4-GDD of type $4^t 7^s$ for all but a finite specified set of feasible values for $(t,…

Combinatorics · Mathematics 2024-01-23 R. Julian R. Abel , Thomas Britz , Yudhistira A. Bunjamin , Diana Combe

We study $k$-uniform states in heterogeneous systems whose local dimensions are mixed. Based on the connections between mixed orthogonal arrays with certain minimum Hamming distance, irredundant mixed orthogonal arrays and $k$-uniform…

Quantum Physics · Physics 2020-06-09 Fei Shi , Yi Shen , Lin Chen , Xiande Zhang

Twisted permutation codes, introduced recently by the second and third authors, are frequency permutation arrays. They are similar to repetition permutation codes, in that they are obtained by a repetition construction applied to a smaller…

Combinatorics · Mathematics 2015-11-24 Marzieh Akbari , Neil I. Gillespie , Cheryl E. Praeger

The $q$-analogs of basic designs are discussed. It is proved that the existence of any unknown Steiner structures, the $q$-analogs of Steiner systems, implies the existence of unknown Steiner systems. Optimal $q$-analogs covering designs…

Combinatorics · Mathematics 2015-03-13 Tuvi Etzion , Alexander Vardy

The quantum systems with finite-dimensional Hilbert space have several applications and are intensively explored theoretically and experimentally. The mathematical description of these systems follows the analogy with the usual…

Quantum Physics · Physics 2023-05-30 Nicolae Cotfas

The Fermat--Steiner problem is to find all points of the metric space Y such that the sum of the distances from each of them to points from some fixed finite subset A = {A_1, ..., A_n} of the space Y is minimal. This problem is considered…

Metric Geometry · Mathematics 2022-12-06 A. Kh. Galstyan

A Kirkman triple system of order $v$, KTS$(v)$, is a resolvable Steiner triple system on $v$ elements. In this paper, we investigate an open problem posed by Doug Stinson, namely the existence of KTS$(v)$ which contain as a subdesign a…

Combinatorics · Mathematics 2021-10-18 Peter Dukes , Esther Lamken

The Gromov-Wasserstein (GW) distance is frequently used in machine learning to compare distributions across distinct metric spaces. Despite its utility, it remains computationally intensive, especially for large-scale problems. Recently, a…

Machine Learning · Statistics 2024-10-01 Antoine Salmona , Julie Delon , Agnès Desolneux