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We present a randomized $\tilde{O}(n^{3.5})$-time algorithm for computing \emph{optimal energetic paths} for an electric car between all pairs of vertices in an $n$-vertex directed graph with positive and negative \emph{costs}. The optimal…

Data Structures and Algorithms · Computer Science 2025-05-05 Dani Dorfman , Haim Kaplan , Robert E. Tarjan , Mikkel Thorup , Uri Zwick

The study of approximate matching in the Massively Parallel Computations (MPC) model has recently seen a burst of breakthroughs. Despite this progress, however, we still have a far more limited understanding of maximal matching which is one…

Data Structures and Algorithms · Computer Science 2023-10-17 Soheil Behnezhad , MohammadTaghi Hajiaghayi , David G. Harris

We present an $\tilde{O}\left(m^{\frac{10}{7}}U^{\frac{1}{7}}\right)$-time algorithm for the maximum $s$-$t$ flow problem and the minimum $s$-$t$ cut problem in directed graphs with $m$ arcs and largest integer capacity $U$. This matches…

Data Structures and Algorithms · Computer Science 2016-08-23 Aleksander Madry

We present an algorithm for maintaining maximal matching in a graph under addition and deletion of edges. Our data structure is randomized that takes O(log n) expected amortized time for each edge update where n is the number of vertices in…

Data Structures and Algorithms · Computer Science 2016-08-03 Surender Baswana , Manoj Gupta , Sandeep Sen

Random graph matching refers to recovering the underlying vertex correspondence between two random graphs with correlated edges; a prominent example is when the two random graphs are given by Erd\H{o}s-R\'{e}nyi graphs $G(n,\frac{d}{n})$.…

Machine Learning · Statistics 2020-07-21 Jian Ding , Zongming Ma , Yihong Wu , Jiaming Xu

We consider the problem of maintaining an approximate maximum integral matching in a dynamic graph $G$, while the adversary makes changes to the edges of the graph. The goal is to maintain a $(1+\epsilon)$-approximate maximum matching for…

Data Structures and Algorithms · Computer Science 2022-07-07 Sepehr Assadi , Aaron Bernstein , Aditi Dudeja

Computing all-pairs shortest paths is a fundamental and much-studied problem with many applications. Unfortunately, despite intense study, there are still no significantly faster algorithms for it than the $\mathcal{O}(n^3)$ time algorithm…

Data Structures and Algorithms · Computer Science 2020-01-15 Stefan Kratsch , Florian Nelles

We give an algorithm to find a mincut in an $n$-vertex, $m$-edge weighted directed graph using $\tilde O(\sqrt{n})$ calls to any maxflow subroutine. Using state of the art maxflow algorithms, this yields a directed mincut algorithm that…

Data Structures and Algorithms · Computer Science 2021-04-19 Ruoxu Cen , Jason Li , Danupon Nanongkai , Debmalya Panigrahi , Thatchaphol Saranurak

Connectivity (or equivalently, unweighted maximum flow) is an important measure in graph theory and combinatorial optimization. Given a graph $G$ with vertices $s$ and $t$, the connectivity $\lambda(s,t)$ from $s$ to $t$ is defined to be…

Data Structures and Algorithms · Computer Science 2024-12-25 Shyan Akmal

We study the Minimum Crossing Number problem: given an $n$-vertex graph $G$, the goal is to find a drawing of $G$ in the plane with minimum number of edge crossings. This is one of the central problems in topological graph theory, that has…

Data Structures and Algorithms · Computer Science 2010-12-02 Julia Chuzhoy

We present an $m^{4/3+o(1)}\log W$-time algorithm for solving the minimum cost flow problem in graphs with unit capacity, where $W$ is the maximum absolute value of any edge weight. For sparse graphs, this improves over the best known…

Data Structures and Algorithms · Computer Science 2020-04-10 Kyriakos Axiotis , Aleksander Mądry , Adrian Vladu

Given a simple weighted directed graph $G = (V, E, \omega)$ on $n$ vertices as well as two designated terminals $s, t\in V$, our goal is to compute the shortest path from $s$ to $t$ avoiding any pair of presumably failed edges $f_1, f_2\in…

Data Structures and Algorithms · Computer Science 2024-04-23 Shiri Chechik , Tianyi Zhang

For a graph G=(V,E), finding a set of disjoint edges that do not share any vertices is called a matching problem, and finding the maximum matching is a fundamental problem in the theory of distributed graph algorithms. Although local…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-03-14 Naoki Kitamura , Taisuke Izumi

We present a family of fast pseudo-approximation algorithms for the minimum balanced vertex separator problem in a graph. Given a graph $G=(V,E)$ with $n$ vertices and $m$ edges, and a (constant) balance parameter $c\in(0,1/2)$, where $G$…

Data Structures and Algorithms · Computer Science 2026-03-18 Vladimir Kolmogorov , Jack Spalding-Jamieson

This paper shows the weighted matching problem on general graphs can be solved in time $O(n(m + n\log n))$ for $n$ and $m$ the number of vertices and edges, respectively. This was previously known only for bipartite graphs. The crux is a…

Data Structures and Algorithms · Computer Science 2016-11-24 Harold N. Gabow

Identifying the connected components of a graph, apart from being a fundamental problem with countless applications, is a key primitive for many other algorithms. In this paper, we consider this problem in parallel settings. Particularly,…

Data Structures and Algorithms · Computer Science 2020-03-13 Soheil Behnezhad , Laxman Dhulipala , Hossein Esfandiari , Jakub Łącki , Vahab Mirrokni

We give efficient distributed algorithms for the minimum vertex cover problem in bipartite graphs in the CONGEST model. From K\H{o}nig's theorem, it is well known that in bipartite graphs the size of a minimum vertex cover is equal to the…

Data Structures and Algorithms · Computer Science 2020-11-20 Salwa Faour , Fabian Kuhn

We give a deterministic algorithm for computing a global minimum vertex cut in a vertex-weighted graph $n$ vertices and $m$ edges in $\widehat O(mn)$ time. This breaks the long-standing $\widehat \Omega(n^{4})$-time barrier in dense graphs,…

Data Structures and Algorithms · Computer Science 2025-03-28 Yonggang Jiang , Chaitanya Nalam , Thatchaphol Saranurak , Sorrachai Yingchareonthawornchai

We describe approximation algorithms in Linial's classic LOCAL model of distributed computing to find maximum-weight matchings in a hypergraph of rank $r$. Our main result is a deterministic algorithm to generate a matching which is an…

Data Structures and Algorithms · Computer Science 2023-10-13 David G. Harris

In a seminal paper on finding large matchings in sparse random graphs, Karp and Sipser proposed two algorithms for this task. The second algorithm has been intensely studied, but due to technical difficulties, the first algorithm has…

Combinatorics · Mathematics 2018-11-14 Michael Anastos , Alan Frieze