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Context: Detecting arrays are mathematical structures aimed at fault identification in combinatorial interaction testing. However, they cannot be directly applied to systems that have constraints among test parameters. Such constraints are…

Software Engineering · Computer Science 2021-10-14 Hao Jin , Ce Shi , Tatsuhiro Tsuchiya

The enormous amount of data to be represented using large graphs exceeds in some cases the resources of a conventional computer. Edges in particular can take up a considerable amount of memory as compared to the number of nodes. However,…

Artificial Intelligence · Computer Science 2023-12-18 Faisal N. Abu-Khzam , Rana H. Mouawi , Amer Hajj Ahmad , Sergio Thoumi

We study Cayley configuration spaces of a class of 1 degree-of-freedom linkages (graphs with specified edge lengths), obtained by dropping an edge from a tree-decomposable graph. The class includes well-known mechanisms based on the…

Computational Geometry · Computer Science 2025-11-04 Meera Sitharam , Menghan Wang , William Sims , Heping Gao

A common representation of a three dimensional object in computer applications, such as graphics and design, is in the form of a triangular mesh. In many instances, individual or groups of triangles in such representation need to satisfy…

Optimization and Control · Mathematics 2019-04-08 Valentin R. Koch , Hung M. Phan

Graph learning from data represents a canonical problem that has received substantial attention in the literature. However, insufficient work has been done in incorporating prior structural knowledge onto the learning of underlying…

Machine Learning · Statistics 2019-04-23 Sandeep Kumar , Jiaxi Ying , José Vinícius de M. Cardoso , Daniel Palomar

A realization of a graph $G=(V,E)$ is a map $v\colon V\to\Bbb R^d$ that assigns to each vertex a point in $d$-dimensional Euclidean space. We study graph realizations from the perspective of representation theory (expressing certain…

Combinatorics · Mathematics 2020-09-04 Martin Winter

The graphical notion of effective resistance has found wide-ranging applications in many areas of pure mathematics, applied mathematics and control theory. By the nature of its construction, effective resistance can only be computed in…

Optimization and Control · Mathematics 2013-10-23 George Forrest Young , Luca Scardovi , Naomi Ehrich Leonard

We propose a new embedding method which is particularly well-suited for settings where the sample size greatly exceeds the ambient dimension. Our technique consists of partitioning the space into simplices and then embedding the data points…

Machine Learning · Computer Science 2020-02-07 Lee-Ad Gottlieb , Eran Kaufman , Aryeh Kontorovich , Gabriel Nivasch , Ofir Pele

The paper introduces a special case of the Euclidean distance matrix completion problem (edmcp) of interest in statistical data analysis where only the minimal spanning tree distances are given and the matrix completion must preserve the…

Optimization and Control · Mathematics 2016-10-24 Adam Rahman , Wayne Oldford

We study shortest paths and their distances on a subset of a Euclidean space, and their approximation by their equivalents in a neighborhood graph defined on a sample from that subset. In particular, we recover and extend the results of…

Computational Geometry · Computer Science 2018-10-26 Ery Arias-Castro , Thibaut Le Gouic

We continue to study Cayley configuration spaces of 1-dof linkages in 2D begun in Part I of this paper, i.e. the set of attainable lengths for a non-edge. In Part II, we focus on the algebraic complexity of describing endpoints of the…

Computational Geometry · Computer Science 2015-03-19 Meera Sitharam , Menghan Wang , Heping Gao

Topological features based on persistent homology capture high-order structural information so as to augment graph neural network methods. However, computing extended persistent homology summaries remains slow for large and dense graphs and…

Machine Learning · Computer Science 2022-11-16 Zuoyu Yan , Tengfei Ma , Liangcai Gao , Zhi Tang , Yusu Wang , Chao Chen

An important problem that commonly arises in areas such as internet traffic-flow analysis, phylogenetics and electrical circuit design, is to find a representation of any given metric $D$ on a finite set by an edge-weighted graph, such that…

Metric Geometry · Mathematics 2014-12-23 Sven Herrmann , Vincent Moulton , Andreas Spillner

We describe the structure of connected graphs with the minimum and maximum average distance, radius, diameter, betweenness centrality, efficiency and resistance distance, given their order and size. We find tight bounds on these graph…

Molecular Networks · Quantitative Biology 2011-05-02 Dionysios Barmpoutis , Richard M. Murray

We introduce a new family of closed differential forms naturally associated with minimal graphical submanifolds in Euclidean space, defined in arbitrary codimension. For each minimal graph, we construct an explicit closed form whose…

Differential Geometry · Mathematics 2026-04-07 Chung-Jun Tsai , Mu-Tao Wang

Graph rigidity theory studies the capability of a graph embedded in the Euclidean space to constrain its global geometric shape via local constraints among nodes and edges, and has been widely exploited in network localization and formation…

Optimization and Control · Mathematics 2025-06-05 Jinpeng Huang , Gangshan Jing

For configurations of point-sets that are pairwise constrained by distance intervals, the EASAL software implements a suite of algorithms that characterize the structure and geometric properties of the configuration space. The algorithms…

Computational Geometry · Computer Science 2018-06-06 Aysegul Ozkan , Rahul Prabhu , Troy Baker , James Pence , Jorg Peters , Meera Sitharam

Geometric modeling by constraints, whose applications are of interest to communities from various fields such as mechanical engineering, computer aided design, symbolic computation or molecular chemistry, is now integrated into standard…

Computational Geometry · Computer Science 2018-03-06 Samy Ait-Aoudia , Adel Moussaoui , Khaled Abid , Dominique Michelucci

The chain graph model admits both undirected and directed edges in one graph, where symmetric conditional dependencies are encoded via undirected edges and asymmetric causal relations are encoded via directed edges. Though frequently…

Methodology · Statistics 2024-01-29 Ruixuan Zhao , Haoran Zhang , Junhui Wang

This paper considers the problem of embedding directed graphs in Euclidean space while retaining directional information. We model a directed graph as a finite set of observations from a diffusion on a manifold endowed with a vector field.…

Machine Learning · Statistics 2014-06-03 Dominique Perrault-Joncas , Marina Meila