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We present algorithms for solving a large class of flow and regression problems on unit weighted graphs to $(1 + 1 / poly(n))$ accuracy in almost-linear time. These problems include $\ell_p$-norm minimizing flow for $p$ large ($p \in…

Data Structures and Algorithms · Computer Science 2019-06-26 Rasmus Kyng , Richard Peng , Sushant Sachdeva , Di Wang

We present faster high-accuracy algorithms for computing $\ell_p$-norm minimizing flows. On a graph with $m$ edges, our algorithm can compute a $(1+1/\text{poly}(m))$-approximate unweighted $\ell_p$-norm minimizing flow with…

Data Structures and Algorithms · Computer Science 2020-01-10 Deeksha Adil , Sushant Sachdeva

We present a nearly-linear time algorithm that produces high-quality sparsifiers of weighted graphs. Given as input a weighted graph $G=(V,E,w)$ and a parameter $\epsilon>0$, we produce a weighted subgraph $H=(V,\tilde{E},\tilde{w})$ of $G$…

Data Structures and Algorithms · Computer Science 2009-11-18 Daniel A. Spielman , Nikhil Srivastava

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

We present the first almost-linear time algorithm for constructing linear-sized spectral sparsification for graphs. This improves all previous constructions of linear-sized spectral sparsification, which requires $\Omega(n^2)$ time. A key…

Data Structures and Algorithms · Computer Science 2015-08-14 Yin Tat Lee , He Sun

In this paper, we introduce a new framework for approximately solving flow problems in capacitated, undirected graphs and apply it to provide asymptotically faster algorithms for the maximum $s$-$t$ flow and maximum concurrent…

Data Structures and Algorithms · Computer Science 2013-09-24 Jonathan A. Kelner , Yin Tat Lee , Lorenzo Orecchia , Aaron Sidford

In this paper we introduce a notion of spectral approximation for directed graphs. While there are many potential ways one might define approximation for directed graphs, most of them are too strong to allow sparse approximations in…

Data Structures and Algorithms · Computer Science 2016-11-03 Michael B. Cohen , Jonathan Kelner , John Peebles , Richard Peng , Anup Rao , Aaron Sidford , Adrian Vladu

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

We study vertex sparsification for distances, in the setting of planar graphs with distortion: Given a planar graph $G$ (with edge weights) and a subset of $k$ terminal vertices, the goal is to construct an $\varepsilon$-emulator, which is…

Data Structures and Algorithms · Computer Science 2022-06-23 Hsien-Chih Chang , Robert Krauthgamer , Zihan Tan

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

The problem of sparsifying a graph or a hypergraph while approximately preserving its cut structure has been extensively studied and has many applications. In a seminal work, Bencz\'ur and Karger (1996) showed that given any $n$-vertex…

Data Structures and Algorithms · Computer Science 2021-06-22 Yu Chen , Sanjeev Khanna , Ansh Nagda

We provide an algorithm that, given an $n$-vertex $m$-edge Eulerian graph with polynomially bounded weights, computes an $\breve{O}(n\log^{2} n \cdot \varepsilon^{-2})$-edge $\varepsilon$-approximate Eulerian sparsifier with high…

Data Structures and Algorithms · Computer Science 2024-08-20 Arun Jambulapati , Sushant Sachdeva , Aaron Sidford , Kevin Tian , Yibin Zhao

We initiate the study of dynamic algorithms for graph sparsification problems and obtain fully dynamic algorithms, allowing both edge insertions and edge deletions, that take polylogarithmic time after each update in the graph. Our three…

Data Structures and Algorithms · Computer Science 2018-03-02 Ittai Abraham , David Durfee , Ioannis Koutis , Sebastian Krinninger , Richard Peng

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

The (non-uniform) sparsest cut problem is the following graph-partitioning problem: given a "supply" graph, and demands on pairs of vertices, delete some subset of supply edges to minimize the ratio of the supply edges cut to the total…

Data Structures and Algorithms · Computer Science 2021-06-01 Vincent Cohen-Addad , Anupam Gupta , Philip N. Klein , Jason Li

We give an algorithm that, with high probability, maintains a $(1-\epsilon)$-approximate $s$-$t$ maximum flow in undirected, uncapacitated $n$-vertex graphs undergoing $m$ edge insertions in $\tilde{O}(m+ n F^*/\epsilon)$ total update time,…

Data Structures and Algorithms · Computer Science 2026-05-22 Gramoz Goranci , Monika Henzinger , Harald Räcke , A. R. Sricharan

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 provide an algorithm which, with high probability, maintains a $(1-\epsilon)$-approximate maximum flow on an undirected graph undergoing $m$-edge additions in amortized $m^{o(1)} \epsilon^{-3}$ time per update. To obtain this result, we…

Data Structures and Algorithms · Computer Science 2023-11-07 Jan van den Brand , Li Chen , Rasmus Kyng , Yang P. Liu , Richard Peng , Maximilian Probst Gutenberg , Sushant Sachdeva , Aaron Sidford

We study the problem of graph and hypergraph sparsification in insertion-only data streams. The input is a hypergraph $H=(V, E, w)$ with $n$ nodes, $m$ hyperedges, and rank $r$, and the goal is to compute a hypergraph $\widehat{H}$ that…

Data Structures and Algorithms · Computer Science 2025-10-22 Vincent Cohen-Addad , David P. Woodruff , Shenghao Xie , Samson Zhou

A $(1 \pm \epsilon)$-sparsifier of a hypergraph $G(V,E)$ is a (weighted) subgraph that preserves the value of every cut to within a $(1 \pm \epsilon)$-factor. It is known that every hypergraph with $n$ vertices admits a $(1 \pm…

Data Structures and Algorithms · Computer Science 2024-07-08 Sanjeev Khanna , Aaron L. Putterman , Madhu Sudan
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