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Consider a graph with n nodes and m edges, independent edge weights and lengths, and arbitrary distance demands for node pairs. The spanner problem asks for a minimum-weight subgraph that satisfies these demands via sufficiently short paths…

Data Structures and Algorithms · Computer Science 2025-07-02 Fritz Bökler , Markus Chimani , Henning Jasper

Graph spanners are well-studied and widely used both in theory and practice. In a recent breakthrough, Chechik and Wulff-Nilsen [CW18] improved the state-of-the-art for light spanners by constructing a $(2k-1)(1+\epsilon)$-spanner with…

Data Structures and Algorithms · Computer Science 2022-01-20 Stephen Alstrup , Søren Dahlgaard , Arnold Filtser , Morten Stöckel , Christian Wulff-Nilsen

Solomon and Elkin constructed a shortcutting scheme for weighted trees which results in a 1-spanner for the tree metric induced by the input tree. The spanner has logarithmic lightness, logarithmic diameter, a linear number of edges and…

Computational Geometry · Computer Science 2021-09-22 Milutin Brankovic , Joachim Gudmundsson , André van Renssen

In this paper, we study weakly dynamic undirected graphs, that can be used to represent some logistic networks. The goal is to deliver all the delivery points in the network. The network exists in a mostly stable environment, except for a…

Data Structures and Algorithms · Computer Science 2019-04-11 Moustafa Nakechbandi , Jean-Yves Colin , Hervé Mathieu

To our knowledge, there are only two known algorithms for constructing sparse and light spanners for general graphs. One of them is the greedy algorithm of Alth$\ddot{o}$fer et al. \cite{ADDJS93}, analyzed by Chandra et al. in SoCG'92. The…

Data Structures and Algorithms · Computer Science 2012-07-09 Michael Elkin , Shay Solomon

This paper addresses the problem of online learning in metric spaces using exponential weights. We extend the analysis of the exponentially weighted average forecaster, traditionally studied in a Euclidean settings, to a more abstract…

Machine Learning · Statistics 2021-03-29 Quentin Paris

Constructing a spanning tree of a graph is one of the most basic tasks in graph theory. Motivated by several recent studies of local graph algorithms, we consider the following variant of this problem. Let G be a connected bounded-degree…

Combinatorics · Mathematics 2015-02-04 Reut Levi , Guy Moshkovitz , Dana Ron , Ronitt Rubinfeld , Asaf Shapira

We study the sublinear multivariate mean estimation problem in $d$-dimensional Euclidean space. Specifically, we aim to find the mean $\mu$ of a ground point set $A$, which minimizes the sum of squared Euclidean distances of the points in…

Data Structures and Algorithms · Computer Science 2025-10-07 Beatrice Bertolotti , Matteo Russo , Chris Schwiegelshohn , Sudarshan Shyam

A tree $t$-spanner of a graph $G$ is a spanning tree of $G$ such that the distance between pairs of vertices in the tree is at most $t$ times their distance in $G$. Deciding tree $t$-spanner admissible graphs has been proved to be tractable…

Discrete Mathematics · Computer Science 2018-01-01 Ioannis Papoutsakis

Inspired by graph-based methodologies, we introduce a novel graph-spanning algorithm designed to identify changes in both offline and online data across low to high dimensions. This versatile approach is applicable to Euclidean and…

Machine Learning · Statistics 2026-01-09 Yang-Wen Sun , Katerina Papagiannouli , Vladimir Spokoiny

Reliable spanners can withstand huge failures, even when a linear number of vertices are deleted from the network. In case of failures, a reliable spanner may have some additional vertices for which the spanner property no longer holds, but…

Computational Geometry · Computer Science 2022-04-25 Kevin Buchin , Sariel Har-Peled , Daniel Olah

A temporal graph is an undirected graph $G=(V,E)$ along with a function that assigns a time-label to each edge in $E$. A path in $G$ with non-decreasing time-labels is called temporal path and the distance from $u$ to $v$ is the minimum…

Data Structures and Algorithms · Computer Science 2022-06-23 Davide Bilò , Gianlorenzo D'Angelo , Luciano Gualà , Stefano Leucci , Mirko Rossi

Fault tolerant distance preservers (spanners) are sparse subgraphs that preserve (approximate) distances between given pairs of vertices under edge or vertex failures. So-far, these structures have been studied mainly from a centralized…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-06 Merav Parter

We attempt to shed new light on the notion of 'tree-like' metric spaces by focusing on an approach that does not use the four-point condition. Our key question is: Given metric space $M$ on $n$ points, when does a fully labelled…

Combinatorics · Mathematics 2015-12-08 Momoko Hayamizu , Kenji Fukumizu

A point set $M$ in $m$-dimensional Euclidean space is called an integral point set if all the distances between the elements of $M$ are integers, and $M$ is not situated on an $(m-1)$-dimensional hyperplane. We improve the linear lower…

Combinatorics · Mathematics 2025-12-02 Nikolai Avdeev

In this paper we study graph problems in dynamic streaming model, where the input is defined by a sequence of edge insertions and deletions. As many natural problems require $\Omega(n)$ space, where $n$ is the number of vertices, existing…

Data Structures and Algorithms · Computer Science 2016-05-03 Zengfeng Huang , Pan Peng

In this work we provide a new technique to design fast approximation algorithms for graph problems where the points of the graph lie in a metric space. Specifically, we present a sampling approach for such metric graphs that, using a…

Data Structures and Algorithms · Computer Science 2018-07-26 Hossein Esfandiari , Michael Mitzenmacher

We consider straight line drawings of a planar graph $G$ with possible edge crossings. The \emph{untangling problem} is to eliminate all edge crossings by moving as few vertices as possible to new positions. Let $fix(G)$ denote the maximum…

Computational Geometry · Computer Science 2011-11-14 Alexander Ravsky , Oleg Verbitsky

VC-dimension and $\varepsilon$-nets are key concepts in Statistical Learning Theory. Intuitively, VC-dimension is a measure of the size of a class of sets. The famous $\varepsilon$-net theorem, a fundamental result in Discrete Geometry,…

Machine Learning · Computer Science 2024-10-10 Sujoy Bhore , Devdan Dey , Satyam Singh

We study the complexity of geometric problems on spaces of low fractal dimension. It was recently shown by [Sidiropoulos & Sridhar, SoCG 2017] that several problems admit improved solutions when the input is a pointset in Euclidean space…

Computational Complexity · Computer Science 2017-12-14 Anastasios Sidiropoulos , Kritika Singhal , Vijay Sridhar