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Let $G = (V,E,w)$ be a weighted undirected graph on $|V| = n$ vertices and $|E| = m$ edges, let $k \ge 1$ be any integer, and let $\epsilon < 1$ be any parameter. We present the following results on fast constructions of spanners with…

Data Structures and Algorithms · Computer Science 2021-08-03 Hung Le , Shay Solomon

A spectral sparsifier of a graph $G$ is a sparser graph $H$ that approximately preserves the quadratic form of $G$, i.e. for all vectors $x$, $x^T L_G x \approx x^T L_H x$, where $L_G$ and $L_H$ denote the respective graph Laplacians.…

Data Structures and Algorithms · Computer Science 2016-11-22 Rasmus Kyng , Jakub Pachocki , Richard Peng , Sushant Sachdeva

Spectral graph sparsification has emerged as a powerful tool in the analysis of large-scale networks by reducing the overall number of edges, while maintaining a comparable graph Laplacian matrix. In this paper, we present an efficient…

Data Structures and Algorithms · Computer Science 2014-12-16 David G. Anderson , Ming Gu , Christopher Melgaard

In a graph $G = (V,E)$, a vertex subset $S\subseteq V(G)$ is said to be a dominating set of $G$ if every vertex not in $S$ is adjacent to a vertex in $S$. A dominating set $S$ of $G$ is called a paired-dominating set of $G$ if the induced…

Data Structures and Algorithms · Computer Science 2016-05-03 Ching-Chi Lin , Cheng-Yu Hsieh

Given an undirected edge-weighted graph $G=(V,E)$ with $m$ edges and $n$ vertices, the minimum cut problem asks to find a subset of vertices $S$ such that the total weight of all edges between $S$ and $V \setminus S$ is minimized. Karger's…

Data Structures and Algorithms · Computer Science 2020-08-07 Paweł Gawrychowski , Shay Mozes , Oren Weimann

We provide the first online algorithm for spectral hypergraph sparsification. In the online setting, hyperedges with positive weights are arriving in a stream, and upon the arrival of each hyperedge, we must irrevocably decide whether or…

Data Structures and Algorithms · Computer Science 2023-11-08 Tasuku Soma , Kam Chuen Tung , Yuichi Yoshida

Cuts in graphs are a fundamental object of study, and play a central role in the study of graph algorithms. The problem of sparsifying a graph while approximately preserving its cut structure has been extensively studied and has many…

Data Structures and Algorithms · Computer Science 2020-09-11 Yu Chen , Sanjeev Khanna , Ansh Nagda

We introduce a new algorithmic framework for designing dynamic graph algorithms in minor-free graphs, by exploiting the structure of such graphs and a tool called vertex sparsification, which is a way to compress large graphs into small…

Data Structures and Algorithms · Computer Science 2017-12-19 Gramoz Goranci , Monika Henzinger , Pan Peng

Let $G = (V,E,\ell)$ be a $n$-node $m$-edge weighted undirected graph, where $\ell: E \rightarrow (0,\infty)$ is a real \emph{length} function defined on its edges, and let $g$ denote the girth of $G$, i.e., the length of its shortest…

Data Structures and Algorithms · Computer Science 2025-07-21 Avi Kadria , Liam Roditty , Aaron Sidford , Virginia Vassilevska Williams , Uri Zwick

In the decremental $(1+\epsilon)$-approximate Single-Source Shortest Path (SSSP) problem, we are given a graph $G=(V,E)$ with $n = |V|, m = |E|$, undergoing edge deletions, and a distinguished source $s \in V$, and we are asked to process…

Data Structures and Algorithms · Computer Science 2020-01-30 Maximilian Probst Gutenberg , Christian Wulff-Nilsen

Motivated by a sampling problem basic to computational statistical inference, we develop a nearly optimal algorithm for a fundamental problem in spectral graph theory and numerical analysis. Given an $n\times n$ SDDM matrix ${\bf…

Data Structures and Algorithms · Computer Science 2014-10-21 Dehua Cheng , Yu Cheng , Yan Liu , Richard Peng , Shang-Hua Teng

A cut sparsifier is a reweighted subgraph that maintains the weights of the cuts of the original graph up to a multiplicative factor of $(1\pm\epsilon)$. This paper considers computing cut sparsifiers of weighted graphs of size $O(n\log…

Data Structures and Algorithms · Computer Science 2022-04-29 Sebastian Forster , Tijn de Vos

In this paper, we present a simple combinatorial algorithm that solves symmetric diagonally dominant (SDD) linear systems in nearly-linear time. It uses very little of the machinery that previously appeared to be necessary for a such an…

Data Structures and Algorithms · Computer Science 2013-01-29 Jonathan A. Kelner , Lorenzo Orecchia , Aaron Sidford , Zeyuan Allen Zhu

In this paper we consider generalized flow problems where there is an $m$-edge $n$-node directed graph $G = (V,E)$ and each edge $e \in E$ has a loss factor $\gamma_e >0$ governing whether the flow is increased or decreased as it crosses…

Data Structures and Algorithms · Computer Science 2025-10-21 Shunhua Jiang , Michael Kapralov , Lawrence Li , Aaron Sidford

We present the first single pass algorithm for computing spectral sparsifiers of graphs in the dynamic semi-streaming model. Given a single pass over a stream containing insertions and deletions of edges to a graph G, our algorithm…

Data Structures and Algorithms · Computer Science 2015-04-17 Michael Kapralov , Yin Tat Lee , Cameron Musco , Christopher Musco , Aaron Sidford

In this paper we consider the problem of computing spectral approximations to graphs in the single pass dynamic streaming model. We provide a linear sketching based solution that given a stream of edge insertions and deletions to a $n$-node…

Data Structures and Algorithms · Computer Science 2019-03-29 Michael Kapralov , Navid Nouri , Aaron Sidford , Jakab Tardos

While in many graph mining applications it is crucial to handle a stream of updates efficiently in terms of {\em both} time and space, not much was known about achieving such type of algorithm. In this paper we study this issue for a…

Data Structures and Algorithms · Computer Science 2015-09-23 Sayan Bhattacharya , Monika Henzinger , Danupon Nanongkai , Charalampos E. Tsourakakis

We consider the problem of estimating the spectral density of the normalized adjacency matrix of an $n$-node undirected graph. We provide a randomized algorithm that, with $O(n\epsilon^{-2})$ queries to a degree and neighbor oracle and in…

Data Structures and Algorithms · Computer Science 2024-06-12 Yujia Jin , Ishani Karmarkar , Christopher Musco , Aaron Sidford , Apoorv Vikram Singh

Computing the winning set for B{\"u}chi objectives in alternating games on graphs is a central problem in computer aided verification with a large number of applications. The long standing best known upper bound for solving the problem is…

Computer Science and Game Theory · Computer Science 2015-03-19 Krishnendu Chatterjee , Monika Henzinger

We revisit a classical graph-theoretic problem, the \textit{single-source shortest-path} (SSSP) problem, in weighted unit-disk graphs. We first propose an exact (and deterministic) algorithm which solves the problem in $O(n \log^2 n)$ time…

Computational Geometry · Computer Science 2019-03-14 Haitao Wang , Jie Xue