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Given a weighted graph $G$ and an error parameter $\epsilon > 0$, the {\em graph sparsification} problem requires sampling edges in $G$ and giving the sampled edges appropriate weights to obtain a sparse graph $G_{\epsilon}$ (containing…

Data Structures and Algorithms · Computer Science 2010-04-26 Ramesh Hariharan , Debmalya Panigrahi

A single-commodity congestion approximator for a graph is a compact data structure that approximately predicts the edge congestion required to route any set of single-commodity flow demands in a network. A hierarchical congestion…

Data Structures and Algorithms · Computer Science 2025-12-22 Monika Henzinger , Robin Münk , Harald Räcke

We introduce a new approach to the maximum flow problem in undirected, capacitated graphs using $\alpha$-\emph{congestion-approximators}: easy-to-compute functions that approximate the congestion required to route single-commodity demands…

Data Structures and Algorithms · Computer Science 2013-04-09 Jonah Sherman

Given a large graph $G$ with a set of its $k$ vertices called terminals, a \emph{quality-$q$ flow sparsifier} is a small graph $G'$ that contains the terminals and preserves all multicommodity flows between them up to some multiplicative…

Data Structures and Algorithms · Computer Science 2026-02-16 Yu Chen , Zihan Tan , Mingyang Yang

A non-trivial minimum cut (NMC) sparsifier is a multigraph $\hat{G}$ that preserves all non-trivial minimum cuts of a given undirected graph $G$. We introduce a flexible data structure for fully dynamic graphs that can efficiently provide…

Data Structures and Algorithms · Computer Science 2025-09-08 Monika Henzinger , Evangelos Kosinas , Robin Münk , Harald Räcke

Given an undirected graph $G$ and an error parameter $\epsilon > 0$, the {\em graph sparsification} problem requires sampling edges in $G$ and giving the sampled edges appropriate weights to obtain a sparse graph $G_{\epsilon}$ with the…

Data Structures and Algorithms · Computer Science 2010-05-06 Ramesh Hariharan , Debmalya Panigrahi

A sparsifier of a graph $G$ (Bencz\'ur and Karger; Spielman and Teng) is a sparse weighted subgraph $\tilde G$ that approximately retains the cut structure of $G$. For general graphs, non-trivial sparsification is possible only by using…

Data Structures and Algorithms · Computer Science 2019-05-07 Nikhil Bansal , Ola Svensson , Luca Trevisan

We present new approaches to constructing graph sparsifiers --- weighted subgraphs for which every cut has the same value as the original graph, up to a factor of $(1 \pm \epsilon)$. Our first approach independently samples each edge $uv$…

Data Structures and Algorithms · Computer Science 2010-08-10 Wai Shing Fung , Nicholas J. A. Harvey

A motif is a frequently occurring subgraph of a given directed or undirected graph $G$. Motifs capture higher order organizational structure of $G$ beyond edge relationships, and, therefore, have found wide applications such as in graph…

Data Structures and Algorithms · Computer Science 2022-09-13 Michael Kapralov , Mikhail Makarov , Sandeep Silwal , Christian Sohler , Jakab Tardos

We present a general framework of designing efficient dynamic approximate algorithms for optimization on undirected graphs. In particular, we develop a technique that, given any problem that admits a certain notion of vertex sparsifiers,…

Data Structures and Algorithms · Computer Science 2020-05-06 Li Chen , Gramoz Goranci , Monika Henzinger , Richard Peng , Thatchaphol Saranurak

We study the following version of cut sparsification. Given a large edge-weighted network $G$ with $k$ terminal vertices, compress it into a smaller network $H$ with the same terminals, such that every minimum terminal cut in $H$…

Data Structures and Algorithms · Computer Science 2019-10-08 Robert Krauthgamer , Havana , Rika

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

A hypergraph spectral sparsifier of a hypergraph $G$ is a weighted subgraph $H$ that approximates the Laplacian of $G$ to a specified precision. Recent work has shown that similar to ordinary graphs, there exist $\widetilde{O}(n)$-size…

Data Structures and Algorithms · Computer Science 2025-02-07 Sanjeev Khanna , Huan Li , Aaron Putterman

Designing dynamic graph algorithms against an adaptive adversary is a major goal in the field of dynamic graph algorithms. While a few such algorithms are known for spanning trees, matchings, and single-source shortest paths, very little…

Data Structures and Algorithms · Computer Science 2020-11-11 Aaron Bernstein , Jan van den Brand , Maximilian Probst Gutenberg , Danupon Nanongkai , Thatchaphol Saranurak , Aaron Sidford , He Sun

We describe a polynomial-time algorithm which, given a graph $G$ with treewidth $t$, approximates the pathwidth of $G$ to within a ratio of $O(t\sqrt{\log t})$. This is the first algorithm to achieve an $f(t)$-approximation for some…

Data Structures and Algorithms · Computer Science 2023-03-13 Carla Groenland , Gwenaël Joret , Wojciech Nadara , Bartosz Walczak

Let $G = (V, E)$ be an undirected connected simple graph on $n$ vertices. A cut-equivalent tree of $G$ is an edge-weighted tree on the same vertex set $V$, such that for any pair of vertices $s, t\in V$, the minimum $(s, t)$-cut in the tree…

Data Structures and Algorithms · Computer Science 2022-07-05 Tianyi Zhang

This paper addresses the problem of designing a sparse {\em fault-tolerant} BFS tree, or {\em FT-BFS tree} for short, namely, a sparse subgraph $T$ of the given network $G$ such that subsequent to the failure of a single edge or vertex, the…

Data Structures and Algorithms · Computer Science 2013-02-22 Merav Parter , David Peleg

Recent years have seen extensive research on directed graph sparsification. In this work, we initiate the study of fast fully dynamic spectral and cut sparsification algorithms for directed graphs. We introduce a new notion of spectral…

Data Structures and Algorithms · Computer Science 2025-07-29 Yibin Zhao

Graph sparsification has been studied extensively over the past two decades, culminating in spectral sparsifiers of optimal size (up to constant factors). Spectral hypergraph sparsification is a natural analogue of this problem, for which…

Data Structures and Algorithms · Computer Science 2021-06-07 Michael Kapralov , Robert Krauthgamer , Jakab Tardos , Yuichi Yoshida

Let $G$ be a graph and $S, T \subseteq V(G)$ be (possibly overlapping) sets of terminals, $|S|=|T|=k$. We are interested in computing a vertex sparsifier for terminal cuts in $G$, i.e., a graph $H$ on a smallest possible number of vertices,…

Data Structures and Algorithms · Computer Science 2021-07-06 Zhiyang He , Jason Li , Magnus Wahlström