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Related papers: On $(1+\varepsilon)$-Approximate Flow Sparsifiers

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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 useful approach to "compress" a large network $G$ is to represent it with a {\em flow-sparsifier}, i.e., a small network $H$ that supports the same flows as $G$, up to a factor $q \geq 1$ called the quality of sparsifier. Specifically, we…

Data Structures and Algorithms · Computer Science 2013-10-14 Alexandr Andoni , Anupam Gupta , Robert Krauthgamer

Flow sparsification is a classic graph compression technique which, given a capacitated graph $G$ on $k$ terminals, aims to construct another capacitated graph $H$, called a flow sparsifier, that preserves, either exactly or approximately,…

Data Structures and Algorithms · Computer Science 2024-09-09 Syamantak Das , Nikhil Kumar , Daniel Vaz

Given a capacitated graph $G = (V,E)$ and a set of terminals $K \subseteq V$, how should we produce a graph $H$ only on the terminals $K$ so that every (multicommodity) flow between the terminals in $G$ could be supported in $H$ with low…

Data Structures and Algorithms · Computer Science 2016-02-04 Matthias Englert , Anupam Gupta , Robert Krauthgamer , Harald Raecke , Inbal Talgam , Kunal Talwar

Given an undirected graph $G=(V,E)$ with edge capacities $c_e\geq 1$ for $e\in E$ and a subset $T$ of $k$ vertices called terminals, we say that a graph $H$ is a quality-$q$ cut sparsifier for $G$ iff $T\subseteq V(H)$, and for any…

Data Structures and Algorithms · Computer Science 2012-04-16 Julia Chuzhoy

We study vertex sparsification for preserving cuts. Given a graph $G$ with a subset $|T|=k$ of its vertices called terminals, a \emph{quality-$q$ cut sparsifier} is a graph $G'$ that contains $T$, such that, for any partition $(T_1,T_2)$ of…

Data Structures and Algorithms · Computer Science 2024-10-18 Yu Chen , Zihan Tan

Given a large edge-capacitated network $G$ and a subset of $k$ vertices called terminals, an (exact) flow sparsifier is a small network $G'$ that preserves (exactly) all multicommodity flows that can be routed between the terminals. Flow…

Data Structures and Algorithms · Computer Science 2022-08-04 Robert Krauthgamer , Ron Mosenzon

A \emph{tree cut-sparsifier} $T$ of quality $\alpha$ of a graph $G$ is a single tree that preserves the capacities of all cuts in the graph up to a factor of $\alpha$. A \emph{tree flow-sparsifier} $T$ of quality $\alpha$ guarantees that…

Data Structures and Algorithms · Computer Science 2026-02-17 Daniel Agassy , Dani Dorfman , Haim Kaplan

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

Given an unweighted tree $T=(V,E)$ with terminals $K \subset V$, we show how to obtain a $2$-quality vertex flow and cut sparsifier $H$ with $V_H = K$. We prove that our result is essentially tight by providing a $2-o(1)$ lower-bound on the…

Data Structures and Algorithms · Computer Science 2016-12-12 Gramoz Goranci , Harald Raecke

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

Graph compression or sparsification is a basic information-theoretic and computational question. A major open problem in this research area is whether $(1+\epsilon)$-approximate cut-preserving vertex sparsifiers with size close to the…

Data Structures and Algorithms · Computer Science 2020-07-16 Parinya Chalermsook , Syamantak Das , Bundit Laekhanukit , Yunbum Kook , Yang P. Liu , Richard Peng , Mark Sellke , Daniel Vaz

Given a directed graph $G = (V, E)$ with $n$ vertices, $m$ edges and a designated source vertex $s\in V$, we consider the question of finding a sparse subgraph $H$ of $G$ that preserves the flow from $s$ up to a given threshold $\lambda$…

Data Structures and Algorithms · Computer Science 2024-04-26 Shivam Bansal , Keerti Choudhary , Harkirat Dhanoa , Harsh Wardhan

Given a graph with non-negative edge weights, there are various ways to interpret the edge weights and induce a metric on the vertices of the graph. A few examples are shortest-path, when interpreting the weights as lengths; resistance…

Data Structures and Algorithms · Computer Science 2021-12-15 Lior Kalman , Robert Krauthgamer

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

Graph Sparsification aims at compressing large graphs into smaller ones while preserving important characteristics of the input graph. In this work we study Vertex Sparsifiers, i.e., sparsifiers whose goal is to reduce the number of…

Data Structures and Algorithms · Computer Science 2017-12-29 Gramoz Goranci , Monika Henzinger , Pan Peng

We devise new cut sparsifiers that are related to the classical sparsification of Nagamochi and Ibaraki [Algorithmica, 1992], which is an algorithm that, given an unweighted graph $G$ on $n$ nodes and a parameter $k$, computes a subgraph…

Data Structures and Algorithms · Computer Science 2021-11-01 Amir Abboud , Robert Krauthgamer , Ohad Trabelsi

A graph G'(V,E') is an \eps-sparsification of G for some \eps>0, if every (weighted) cut in G' is within (1\pm \eps) of the corresponding cut in G. A celebrated result of Benczur and Karger shows that for every undirected graph G, an…

Data Structures and Algorithms · Computer Science 2015-03-17 Ashish Goel , Michael Kapralov , Sanjeev Khanna

We study resistance sparsification of graphs, in which the goal is to find a sparse subgraph (with reweighted edges) that approximately preserves the effective resistances between every pair of nodes. We show that every dense regular…

Data Structures and Algorithms · Computer Science 2015-06-26 Michael Dinitz , Robert Krauthgamer , Tal Wagner

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
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