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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

We introduce the following notion of compressing an undirected graph G with edge-lengths and terminal vertices $R\subseteq V(G)$. A distance-preserving minor is a minor G' (of G) with possibly different edge-lengths, such that $R\subseteq…

Data Structures and Algorithms · Computer Science 2012-08-21 Robert Krauthgamer , Tamar Zondiner

Given an edge-weighted graph $G$ with a set $Q$ of $k$ terminals, a mimicking network is a graph with the same set of terminals that exactly preserves the sizes of minimum cuts between any partition of the terminals. A natural question in…

Data Structures and Algorithms · Computer Science 2018-01-03 Nikolai Karpov , Marcin Pilipczuk , Anna Zych-Pawlewicz

Given a graph where vertices are partitioned into $k$ terminals and non-terminals, the goal is to compress the graph (i.e., reduce the number of non-terminals) using minor operations while preserving terminal distances approximately.The…

Data Structures and Algorithms · Computer Science 2016-12-30 Yun Kuen Cheung , Gramoz Goranci , Monika Henzinger

We show the existence of O(f(c)k) sized vertex sparsifiers that preserve all edge-connectivity values up to c between a set of k terminal vertices, where f(c) is a function that only depends on c, the edge-connectivity value. This…

Data Structures and Algorithms · Computer Science 2019-10-24 Yang P. Liu , Richard Peng , Mark Sellke

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 propose polynomial-time algorithms that sparsify planar and bounded-genus graphs while preserving optimal or near-optimal solutions to Steiner problems. Our main contribution is a polynomial-time algorithm that, given an unweighted graph…

Data Structures and Algorithms · Computer Science 2017-07-12 Marcin Pilipczuk , Michał Pilipczuk , Piotr Sankowski , Erik Jan van Leeuwen

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

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

In vertex-cut sparsification, given a graph $G=(V,E)$ with a terminal set $T\subseteq V$, we wish to construct a graph $G'=(V',E')$ with $T\subseteq V'$, such that for every two sets of terminals $A,B\subseteq T$, the size of a minimum…

Data Structures and Algorithms · Computer Science 2022-07-05 Itai Boneh , Robert Krauthgamer

A $k$-spanner of a graph $G$ is a sparse subgraph $H$ whose shortest path distances match those of $G$ up to a multiplicative error $k$. In this paper we study spanners that are resistant to faults. A subgraph $H \subseteq G$ is an $f$…

Data Structures and Algorithms · Computer Science 2017-10-10 Greg Bodwin , Michael Dinitz , Merav Parter , Virginia Vassilevska Williams

A \emph{sparsification} of a given graph $G$ is a sparser graph (typically a subgraph) which aims to approximate or preserve some property of $G$. Examples of sparsifications include but are not limited to spanning trees, Steiner trees,…

Data Structures and Algorithms · Computer Science 2023-01-31 Reyan Ahmed , Keaton Hamm , Stephen Kobourov , Mohammad Javad Latifi Jebelli , Faryad Darabi Sahneh , Richard Spence

We consider a variation of the spectral sparsification problem where we are required to keep a subgraph of the original graph. Formally, given a union of two weighted graphs $G$ and $W$ and an integer $k$, we are asked to find a $k$-edge…

Discrete Mathematics · Computer Science 2009-12-10 Alexandra Kolla , Yury Makarychev , Amin Saberi , Shanghua Teng

As graphs scale to billions of nodes and edges, graph Machine Learning workloads are constrained by the cost of multi-hop traversals over exponentially growing neighborhoods. While various system-level and algorithmic optimizations have…

Machine Learning · Computer Science 2026-03-10 Yuhang Song , Naima Abrar Shami , Romaric Duvignau , Vasiliki Kalavri

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

In the Steiner point removal (SPR) problem, we are given a (weighted) graph $G$ and a subset $T$ of its vertices called terminals, and the goal is to compute a (weighted) graph $H$ on $T$ that is a minor of $G$, such that the distance…

Data Structures and Algorithms · Computer Science 2023-10-13 Yu Chen , Zihan Tan

We give almost-linear-time algorithms for constructing sparsifiers with $n\ poly(\log n)$ edges that approximately preserve weighted $(\ell^{2}_2 + \ell^{p}_p)$ flow or voltage objectives on graphs. For flow objectives, this is the first…

Data Structures and Algorithms · Computer Science 2021-02-16 Deeksha Adil , Brian Bullins , Rasmus Kyng , Sushant Sachdeva

We present faster algorithms for approximate maximum flow in undirected graphs with good separator structures, such as bounded genus, minor free, and geometric graphs. Given such a graph with $n$ vertices, $m$ edges along with a recursive…

Data Structures and Algorithms · Computer Science 2012-10-19 Gary Miller , Richard Peng

In this paper we initiate the study of expander decompositions of a graph $G=(V, E)$ in the streaming model of computation. The goal is to find a partitioning $\mathcal{C}$ of vertices $V$ such that the subgraphs of $G$ induced by the…

Data Structures and Algorithms · Computer Science 2023-08-04 Arnold Filtser , Michael Kapralov , Mikhail Makarov

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