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This paper presents a randomized algorithm for the problem of single-source shortest paths on directed graphs with real (both positive and negative) edge weights. Given an input graph with $n$ vertices and $m$ edges, the algorithm completes…

Data Structures and Algorithms · Computer Science 2023-11-14 Jeremy T. Fineman

The $\mathsf{HYBRID}$ model, introduced in [Augustine et al., SODA '20], provides a theoretical foundation for networks that allow multiple communication modes. The model follows the principles of synchronous message passing, whereas nodes…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-05 Fabian Kuhn , Philipp Schneider

We give an algorithm for finding the arboricity of a weighted, undirected graph, defined as the minimum number of spanning forests that cover all edges of the graph, in $\sqrt{n} m^{1+o(1)}$ time. This improves on the previous best bound of…

Data Structures and Algorithms · Computer Science 2025-07-22 Ruoxu Cen , Henry Fleischmann , George Z. Li , Jason Li , Debmalya Panigrahi

We present a low-energy deterministic distributed algorithm that computes exact Single-Source Shortest Paths (SSSP) in near-optimal time: it runs in $\tilde{O}(n)$ rounds and each node is awake during only $poly(\log n)$ rounds. When a node…

Data Structures and Algorithms · Computer Science 2024-09-25 Mohsen Ghaffari , Anton Trygub

We give a simple algorithm for maintaining a $n^{o(1)}$-approximate spanner $H$ of a graph $G$ with $n$ vertices as $G$ receives edge updates by reduction to the dynamic All-Pairs Shortest Paths (APSP) problem. Given an initially empty…

Data Structures and Algorithms · Computer Science 2024-08-22 Rasmus Kyng , Simon Meierhans , Gernot Zöcklein

Graph algorithms are widely used for decision making and knowledge discovery. To ensure their effectiveness, it is essential that their output remains stable even when subjected to small perturbations to the input because frequent output…

Data Structures and Algorithms · Computer Science 2023-09-15 Soh Kumabe , Yuichi Yoshida

We consider the classical Minimum Balanced Cut problem: given a graph $G$, compute a partition of its vertices into two subsets of roughly equal volume, while minimizing the number of edges connecting the subsets. We present the first {\em…

Data Structures and Algorithms · Computer Science 2020-05-05 Julia Chuzhoy , Yu Gao , Jason Li , Danupon Nanongkai , Richard Peng , Thatchaphol Saranurak

The single-source shortest path problem (SSSP) with nonnegative edge weights is a notoriously difficult problem to solve efficiently in parallel---it is one of the graph problems said to suffer from the transitive-closure bottleneck. In…

Data Structures and Algorithms · Computer Science 2016-03-15 Guy E. Blelloch , Yan Gu , Yihan Sun , Kanat Tangwongsan

We describe a new forward-backward variant of Dijkstra's and Spira's Single-Source Shortest Paths (SSSP) algorithms. While essentially all SSSP algorithm only scan edges forward, the new algorithm scans some edges backward. The new…

Data Structures and Algorithms · Computer Science 2014-05-30 David B. Wilson , Uri Zwick

Recently [Bhattacharya et al., STOC 2015] provide the first non-trivial algorithm for the densest subgraph problem in the streaming model with additions and deletions to its edges, i.e., for dynamic graph streams. They present a…

Data Structures and Algorithms · Computer Science 2015-07-30 Hossein Esfandiari , MohammadTaghi Hajiaghayi , David P. Woodruff

We consider the problem of maintaining an approximately maximum (fractional) matching and an approximately minimum vertex cover in a dynamic graph. Starting with the seminal paper by Onak and Rubinfeld [STOC 2010], this problem has received…

Data Structures and Algorithms · Computer Science 2017-04-11 Sayan Bhattacharya , Monika Henzinger , Danupon Nanongkai

We study the use of machine learning techniques to solve a fundamental shortest path problem, known as the single-source many-targets shortest path problem (SSMTSP). Given a directed graph with non-negative edge weights, our goal is to…

Data Structures and Algorithms · Computer Science 2023-03-07 Willem Feijen , Guido Schäfer

Given an arbitrary, non-negatively weighted, directed graph $G=(V,E)$ we present an algorithm that computes all pairs shortest paths in time $\mathcal{O}(m^* n + m \lg n + nT_\psi(m^*, n))$, where $m^*$ is the number of different edges…

Data Structures and Algorithms · Computer Science 2013-01-01 Andrej Brodnik , Marko Grgurovič

Given a graph with a source vertex $s$, the Single Source Replacement Paths (SSRP) problem is to compute, for every vertex $t$ and edge $e$, the length $d(s,t,e)$ of a shortest path from $s$ to $t$ that avoids $e$. A Single-Source Distance…

Data Structures and Algorithms · Computer Science 2021-07-01 Davide Bilò , Sarel Cohen , Tobias Friedrich , Martin Schirneck

In a directed graph $G=(V,E)$ with a capacity on every edge, a \emph{bottleneck path} (or \emph{widest path}) between two vertices is a path maximizing the minimum capacity of edges in the path. For the single-source all-destination version…

Data Structures and Algorithms · Computer Science 2018-09-03 Ran Duan , Kaifeng Lyu , Hongxun Wu , Yuanhang Xie

We give an algorithm that takes a directed graph $G$ undergoing $m$ edge insertions with lengths in $[1, W]$, and maintains $(1+\epsilon)$-approximate shortest path distances from a fixed source $s$ to all other vertices. The algorithm is…

Data Structures and Algorithms · Computer Science 2025-06-25 Yang P. Liu

A stable or locally-optimal cut of a graph is a cut whose weight cannot be increased by changing the side of a single vertex. In this paper we study Minimum Stable Cut, the problem of finding a stable cut of minimum weight. Since this…

Computational Complexity · Computer Science 2026-04-08 Michael Lampis

Computing the Strongly-Connected Components (SCCs) in a graph $G=(V,E)$ is known to take only $O(m + n)$ time using an algorithm by Tarjan from 1972[SICOMP 72] where $m = |E|$, $n=|V|$. For fully-dynamic graphs, conditional lower bounds…

Data Structures and Algorithms · Computer Science 2019-03-15 Aaron Bernstein , Maximilian Probst , Christian Wulff-Nilsen

The Sparsest Cut is a fundamental optimization problem that has been extensively studied. For planar inputs the problem is in $P$ and can be solved in $\tilde{O}(n^3)$ time if all vertex weights are $1$. Despite a significant amount of…

Data Structures and Algorithms · Computer Science 2020-07-07 Amir Abboud , Vincent Cohen-Addad , Philip N. Klein

We consider the problem of finding a minimum cut of a weighted graph presented as a single-pass stream. While graph sparsification in streams has been intensively studied, the specific application of finding minimum cuts in streams is less…

Data Structures and Algorithms · Computer Science 2024-12-09 Matthew Ding , Alexandro Garces , Jason Li , Honghao Lin , Jelani Nelson , Vihan Shah , David P. Woodruff
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