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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

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 propose a simple and natural approximation algorithm for the problem of finding a 2-edge-connected spanning subgraph of minimum total edge cost in a graph. The algorithm maintains a spanning forest starting with an empty edge set. In…

Data Structures and Algorithms · Computer Science 2018-11-21 Stephan Beyer , Markus Chimani , Joachim Spoerhase

We show how to solve directed Laplacian systems in nearly-linear time. Given a linear system in an $n \times n$ Eulerian directed Laplacian with $m$ nonzero entries, we show how to compute an $\epsilon$-approximate solution in time $O(m…

Data Structures and Algorithms · Computer Science 2018-11-28 Michael B. Cohen , Jonathan Kelner , Rasmus Kyng , John Peebles , Richard Peng , Anup B. Rao , Aaron Sidford

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

Diffusion is a fundamental graph procedure and has been a basic building block in a wide range of theoretical and empirical applications such as graph partitioning and semi-supervised learning on graphs. In this paper, we study…

Data Structures and Algorithms · Computer Science 2021-06-07 Li Chen , Richard Peng , Di Wang

We give the first almost-linear total time algorithm for deciding if a flow of cost at most $F$ still exists in a directed graph, with edge costs and capacities, undergoing decremental updates, i.e., edge deletions, capacity decreases, and…

Data Structures and Algorithms · Computer Science 2024-07-16 Jan van den Brand , Li Chen , Rasmus Kyng , Yang P. Liu , Simon Meierhans , Maximilian Probst Gutenberg , Sushant Sachdeva

The Sparsest Cut is a fundamental optimization problem that has been extensively studied. For planar inputs the problem is in $P$ and can be solved in $\tilde{O}(n^3)$ time if all vertex weights are $1$. Despite a significant amount of…

Data Structures and Algorithms · Computer Science 2020-07-07 Amir Abboud , Vincent Cohen-Addad , Philip N. Klein

In the decremental single-source shortest paths problem, the goal is to maintain distances from a fixed source $s$ to every vertex $v$ in an $m$-edge graph undergoing edge deletions. In this paper, we conclude a long line of research on…

Data Structures and Algorithms · Computer Science 2021-01-20 Aaron Bernstein , Maximilian Probst Gutenberg , Thatchaphol Saranurak

We present a parallel algorithm for the $(1-\epsilon)$-approximate maximum flow problem in capacitated, undirected graphs with $n$ vertices and $m$ edges, achieving $O(\epsilon^{-3}\text{polylog} n)$ depth and $O(m \epsilon^{-3}…

Data Structures and Algorithms · Computer Science 2024-02-26 Arpit Agarwal , Sanjeev Khanna , Huan Li , Prathamesh Patil , Chen Wang , Nathan White , Peilin Zhong

In this article, we present the first deterministic directed Laplacian L systems solver that runs in time almost-linear in the number of non-zero entries of L. Previous reductions imply the first deterministic almost-linear time algorithms…

Data Structures and Algorithms · Computer Science 2022-08-24 Rasmus Kyng , Simon Meierhans , Maximilian Probst Gutenberg

The ubiquity of massive graph data sets in numerous applications requires fast algorithms for extracting knowledge from these data. We are motivated here by three electrical measures for the analysis of large small-world graphs $G = (V, E)$…

Data Structures and Algorithms · Computer Science 2021-02-09 Eugenio Angriman , Maria Predari , Alexander van der Grinten , Henning Meyerhenke

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

Whether or not the Sparsest Cut problem admits an efficient $O(1)$-approximation algorithm is a fundamental algorithmic question with connections to geometry and the Unique Games Conjecture. Revisiting spectral algorithms for Sparsest Cut,…

Data Structures and Algorithms · Computer Science 2025-10-01 Tommaso d'Orsi , Chris Jones , Jake Ruotolo , Salil Vadhan , Jiyu Zhang

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

When we try to solve a system of linear equations, we can consider a simple iterative algorithm in which an equation including only one variable is chosen at each step, and the variable is fixed to the value satisfying the equation. The…

Discrete Mathematics · Computer Science 2015-06-03 Ryuhei Mori , Osamu Watanabe

The Laplacian matrix and its pseudo-inverse for a strongly connected directed graph is fundamental in computing many properties of a directed graph. Examples include random-walk centrality and betweenness measures, average hitting and…

Numerical Analysis · Mathematics 2020-09-16 Daniel Boley

In this paper we provide new randomized algorithms with improved runtimes for solving linear programs with two-sided constraints. In the special case of the minimum cost flow problem on $n$-vertex $m$-edge graphs with integer…

Data Structures and Algorithms · Computer Science 2021-08-24 Jan van den Brand , Yin Tat Lee , Yang P. Liu , Thatchaphol Saranurak , Aaron Sidford , Zhao Song , Di Wang

We demonstrate that the best $k$-sparse approximation of a length-$n$ vector can be recovered within a $(1+\epsilon)$-factor approximation in $O((k/\epsilon) \log n)$ time using a non-adaptive linear sketch with $O((k/\epsilon) \log n)$…

Data Structures and Algorithms · Computer Science 2025-10-24 Nick Fischer , Vasileios Nakos

We address long-standing open questions raised by Williamson, Goemans, Vazirani and Mihail pertaining to the design of approximation algorithms for problems in network design via the primal-dual method (Combinatorica 15(3):435-454, 1995).…

Data Structures and Algorithms · Computer Science 2024-01-10 Ishan Bansal , Joseph Cheriyan , Logan Grout , Sharat Ibrahimpur
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