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The area of sublinear algorithms have recently received a lot of attention. In this setting, one has to choose specific access model for the input, as the algorithm does not have time to pre-process or even to see the whole input. A…

Data Structures and Algorithms · Computer Science 2020-09-24 Jakub Tětek

We introduce a new approach to computing an approximately maximum s-t flow in a capacitated, undirected graph. This flow is computed by solving a sequence of electrical flow problems. Each electrical flow is given by the solution of a…

Data Structures and Algorithms · Computer Science 2010-10-20 Paul Christiano , Jonathan A. Kelner , Aleksander Madry , Daniel A. Spielman , Shang-Hua Teng

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

We present an algorithm that given a linear program with $n$ variables, $m$ constraints, and constraint matrix $A$, computes an $\epsilon$-approximate solution in $\tilde{O}(\sqrt{rank(A)}\log(1/\epsilon))$ iterations with high probability.…

Data Structures and Algorithms · Computer Science 2020-09-02 Yin Tat Lee , Aaron Sidford

We use queueing networks to present a new approach to solving Laplacian systems. This marks a significant departure from the existing techniques, mostly based on graph-theoretic constructions and sampling. Our distributed solver works for a…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-09-11 Iqra Altaf Gillani , Amitabha Bagchi

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

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 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

Plotkin, Rao, and Smith (SODA'97) showed that any graph with $m$ edges and $n$ vertices that excludes $K_h$ as a depth $O(\ell\log n)$-minor has a separator of size $O(n/\ell + \ell h^2\log n)$ and that such a separator can be found in…

Data Structures and Algorithms · Computer Science 2014-07-28 Christian Wulff-Nilsen

This paper presents a new deterministic algorithm for single-source shortest paths (SSSP) on real non-negative edge-weighted directed graphs, with running time $O(m\sqrt{\log n}+\sqrt{mn\log n\log \log n})$, which is $O(m\sqrt{\log n\log…

Data Structures and Algorithms · Computer Science 2026-02-11 Ran Duan , Xiao Mao , Xinkai Shu , Longhui Yin

We study distributed algorithms built around minor-based vertex sparsifiers, and give the first algorithm in the CONGEST model for solving linear systems in graph Laplacian matrices to high accuracy. Our Laplacian solver has a round…

Data Structures and Algorithms · Computer Science 2022-02-08 Sebastian Forster , Gramoz Goranci , Yang P. Liu , Richard Peng , Xiaorui Sun , Mingquan Ye

We present a family of fast pseudo-approximation algorithms for the minimum balanced vertex separator problem in a graph. Given a graph $G=(V,E)$ with $n$ vertices and $m$ edges, and a (constant) balance parameter $c\in(0,1/2)$, where $G$…

Data Structures and Algorithms · Computer Science 2026-03-18 Vladimir Kolmogorov , Jack Spalding-Jamieson

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

We give algorithms with running time $2^{O({\sqrt{k}\log{k}})} \cdot n^{O(1)}$ for the following problems. Given an $n$-vertex unit disk graph $G$ and an integer $k$, decide whether $G$ contains (1) a path on exactly/at least $k$ vertices,…

Data Structures and Algorithms · Computer Science 2017-04-25 Fedor V. Fomin , Daniel Lokshtanov , Fahad Panolan , Saket Saurabh , Meirav Zehavi

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

We show an $\widetilde{O}(m^{1.5} \epsilon^{-1})$ time algorithm that on a graph with $m$ edges and $n$ vertices outputs its spanning tree count up to a multiplicative $(1+\epsilon)$ factor with high probability, improving on the previous…

Data Structures and Algorithms · Computer Science 2025-05-21 Yang P. Liu , Richard Peng , Junzhao Yang

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

We provide new algorithms and conditional hardness for the problem of estimating effective resistances in $n$-node $m$-edge undirected, expander graphs. We provide an $\widetilde{O}(m\epsilon^{-1})$-time algorithm that produces with high…

Data Structures and Algorithms · Computer Science 2023-06-27 Rajat Vadiraj Dwaraknath , Ishani Karmarkar , Aaron Sidford

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

We show that preconditioners constructed by random sampling can perform well without meeting the standard requirements of iterative methods. When applied to graph Laplacians, this leads to ultra-sparsifiers that in expectation behave as the…

Data Structures and Algorithms · Computer Science 2014-01-27 Michael B. Cohen , Rasmus Kyng , Jakub W. Pachocki , Richard Peng , Anup Rao