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Given a set of points in the plane, we want to establish a connection network between these points that consists of several disjoint layers. Motivated by sensor networks, we want that each layer is spanning and plane, and that no edge is…

Evolution of large scale networks demand for efficient way of communication in the networks. One way to propagate information in the network is to find vertex cover. In this paper we describe a variant of vertex cover problem naming it…

Data Structures and Algorithms · Computer Science 2016-06-10 Tarun Yadav , Koustav Sadhukhan , Rao Arvind Mallari

The 2-Wasserstein distance (or RMS distance) is a useful measure of similarity between probability distributions that has exciting applications in machine learning. For discrete distributions, the problem of computing this distance can be…

Computational Geometry · Computer Science 2020-07-17 Nathaniel Lahn , Sharath Raghvendra

Geometric matching is an important topic in computational geometry and has been extensively studied over decades. In this paper, we study a geometric-matching problem, known as geometric many-to-many matching. In this problem, the input is…

Computational Geometry · Computer Science 2024-03-06 Sayan Bandyapadhyay , Jie Xue

Quantum circuits composed of CNOT and $R_z$ are fundamental building blocks of many quantum algorithms, so optimizing the synthesis of such quantum circuits is crucial. We address this problem from a theoretical perspective by studying the…

Quantum Physics · Physics 2025-09-15 Yixin Cao , Yiren Lu , Junhong Nie , Xiaoming Sun , Guojing Tian

We study problems related to connecting multi-interface networks of wireless devices. These problems are modeled using graphs, where vertices represent the devices and edges represent potential communication links. Each vertex can activate…

Data Structures and Algorithms · Computer Science 2026-05-11 Michał Szyfelbein , Camille Richer

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

Emerging reconfigurable optical communication technologies allow to enhance datacenter topologies with demand-aware links optimized towards traffic patterns. This paper studies the algorithmic problem of jointly optimizing topology and…

Performance · Computer Science 2024-01-10 Wenkai Dai , Michael Dinitz , Klaus-Tycho Foerster , Long Luo , Stefan Schmid

Sampling edges from a graph in sublinear time is a fundamental problem and a powerful subroutine for designing sublinear-time algorithms. Suppose we have access to the vertices of the graph and know a constant-factor approximation to the…

Data Structures and Algorithms · Computer Science 2022-11-15 Talya Eden , Shyam Narayanan , Jakub Tětek

Finding a minimum spanning tree (MST) for $n$ points in an arbitrary metric space is a fundamental primitive for hierarchical clustering and many other ML tasks, but this takes $\Omega(n^2)$ time to even approximate. We introduce a…

Data Structures and Algorithms · Computer Science 2025-02-19 Nate Veldt , Thomas Stanley , Benjamin W. Priest , Trevor Steil , Keita Iwabuchi , T. S. Jayram , Geoffrey Sanders

The shortest path problem in graphs is a cornerstone of AI theory and applications. Existing algorithms generally ignore edge weight computation time. We present a generalized framework for weighted directed graphs, where edge weight can be…

Data Structures and Algorithms · Computer Science 2024-02-20 Eyal Weiss , Ariel Felner , Gal A. Kaminka

We present parallel algorithms for computing single-source reachability and shortest paths on directed $n$-vertex $m$-edge graphs using near-linear $\tilde{O}(m)$ work and $o(\sqrt{n})$ depth whenever $m\ge n^{1+o(1)}$. At the extreme of…

Data Structures and Algorithms · Computer Science 2026-05-06 Vikrant Ashvinkumar , Aaron Bernstein , Maximilian Probst Gutenberg , Thatchaphol Saranurak

Graph Neural Networks (GNNs) are a powerful representational tool for solving problems on graph-structured inputs. In almost all cases so far, however, they have been applied to directly recovering a final solution from raw inputs, without…

Machine Learning · Statistics 2020-01-16 Petar Veličković , Rex Ying , Matilde Padovano , Raia Hadsell , Charles Blundell

A Monge directed acyclic graph (DAG) $G$ on the nodes $1,2,\cdots,N$ has edges $\left( i,j\right) $ for $1\leq i<j\leq N$ carrying submodular edge-lengths. Finding a shortest $M$-link path from $1$ to $N$ in $G$ for any given $1<M<N-1$ has…

Data Structures and Algorithms · Computer Science 2024-08-02 Joy Z. Wan

In a simple, undirected graph G, an edge 2-coloring is a coloring of the edges such that no vertex is incident to edges with more than 2 distinct colors. The problem maximum edge 2-coloring (ME2C) is to find an edge 2-coloring in a graph G…

Discrete Mathematics · Computer Science 2025-05-07 Tobias Mömke , Alexandru Popa , Aida Roshany-Tabrizi , Michael Ruderer , Roland Vincze

Given two sets of points in the plane, $P$ of $n$ terminals and $S$ of $m$ Steiner points, a Steiner tree of $P$ is a tree spanning all points of $P$ and some (or none or all) points of $S$. A Steiner tree with length of longest edge…

Computational Geometry · Computer Science 2010-12-08 A. Karim Abu-Affash

Estimating the shortest travel time and providing route recommendation between different locations in a city or region can quantitatively measure the conditions of the transportation network during or after extreme events. One common…

Machine Learning · Computer Science 2025-01-20 Tong Liu , Hadi Meidani

A simple and accurate relationship is demonstrated that links the average shortest path, nodes, and edges in a complex network. This relationship takes advantage of the concept of link density and shows a large improvement in fitting…

Physics and Society · Physics 2013-04-24 Reginald D. Smith

This paper studies the problem of embedding very large information networks into low-dimensional vector spaces, which is useful in many tasks such as visualization, node classification, and link prediction. Most existing graph embedding…

Machine Learning · Computer Science 2015-03-13 Jian Tang , Meng Qu , Mingzhe Wang , Ming Zhang , Jun Yan , Qiaozhu Mei

We study the problem of finding small trees. Classical network design problems are considered with the additional constraint that only a specified number $k$ of nodes are required to be connected in the solution. A prototypical example is…

Combinatorics · Mathematics 2009-09-25 R. Ravi , R. Sundaram , Madhav V. Marathe , S. S. Ravi , Daniel J. Rosenkrantz