English
Related papers

Related papers: Towards a better approximation for sparsest cut?

200 papers

We give a 2-approximation algorithm for Non-Uniform Sparsest Cut that runs in time $n^{O(k)}$, where $k$ is the treewidth of the graph. This improves on the previous $2^{2^k}$-approximation in time $\poly(n) 2^{O(k)}$ due to Chlamt\'a\v{c}…

Data Structures and Algorithms · Computer Science 2013-05-08 Anupam Gupta , Kunal Talwar , David Witmer

We study streaming algorithms for the maximum directed cut problem. The edges of an $n$-vertex directed graph arrive one by one in an arbitrary order, and the goal is to estimate the value of the maximum directed cut using a single pass and…

Data Structures and Algorithms · Computer Science 2026-04-01 Amir Azarmehr , Soheil Behnezhad , Shane Ferrante , Mohammad Saneian

We study graph partitioning problems from a min-max perspective, in which an input graph on n vertices should be partitioned into k parts, and the objective is to minimize the maximum number of edges leaving a single part. The two main…

Data Structures and Algorithms · Computer Science 2011-10-21 Nikhil Bansal , Uriel Feige , Robert Krauthgamer , Konstantin Makarychev , Viswanath Nagarajan , Joseph , Naor , Roy Schwartz

We show an $(1+\epsilon)$-approximation algorithm for maintaining maximum $s$-$t$ flow under $m$ edge insertions in $m^{1/2+o(1)} \epsilon^{-1/2}$ amortized update time for directed, unweighted graphs. This constitutes the first sublinear…

Data Structures and Algorithms · Computer Science 2022-11-18 Gramoz Goranci , Monika Henzinger

We present a simple and faster algorithm for computing fair cuts on undirected graphs, a concept introduced in recent work of Li et al. (SODA 2023). Informally, for any parameter $\epsilon>0$, a $(1+\epsilon)$-fair $(s,t)$-cut is an…

Data Structures and Algorithms · Computer Science 2024-12-02 Jason Li , Owen Li

Suppose that we are given an arbitrary graph $G=(V, E)$ and know that each edge in $E$ is going to be realized independently with some probability $p$. The goal in the stochastic matching problem is to pick a sparse subgraph $Q$ of $G$ such…

Data Structures and Algorithms · Computer Science 2020-02-28 Soheil Behnezhad , Mahsa Derakhshan , MohammadTaghi Hajiaghayi

We present improved deterministic algorithms for approximating shortest paths in the Congested Clique model of distributed computing. We obtain $poly(\log\log n)$-round algorithms for the following problems in unweighted undirected…

Data Structures and Algorithms · Computer Science 2020-03-09 Michal Dory , Merav Parter

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

We design fast deterministic algorithms for distance computation in the congested clique model. Our key contributions include: -- A $(2+\epsilon)$-approximation for all-pairs shortest paths in $O(\log^2{n} / \epsilon)$ rounds on unweighted…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-11-01 Keren Censor-Hillel , Michal Dory , Janne H. Korhonen , Dean Leitersdorf

The Max-Cut problem is a fundamental NP-hard problem, which is attracting attention in the field of quantum computation these days. Regarding the approximation algorithm of the Max-Cut problem, algorithms based on semidefinite programming…

Data Structures and Algorithms · Computer Science 2022-03-01 Eiichiro Sato

In the decremental $(1+\epsilon)$-approximate Single-Source Shortest Path (SSSP) problem, we are given a graph $G=(V,E)$ with $n = |V|, m = |E|$, undergoing edge deletions, and a distinguished source $s \in V$, and we are asked to process…

Data Structures and Algorithms · Computer Science 2020-01-30 Maximilian Probst Gutenberg , Christian Wulff-Nilsen

Max-k-Cut and correlation clustering are fundamental graph partitioning problems. For a graph with G=(V,E) with n vertices, the methods with the best approximation guarantees for Max-k-Cut and the Max-Agree variant of correlation clustering…

Optimization and Control · Mathematics 2021-10-28 Nimita Shinde , Vishnu Narayanan , James Saunderson

In this paper, we consider two fundamental cut approximation problems on large graphs. We prove new lower bounds for both problems that are optimal up to logarithmic factors. The first problem is to approximate cuts in balanced directed…

Data Structures and Algorithms · Computer Science 2024-06-21 Yu Cheng , Max Li , Honghao Lin , Zi-Yi Tai , David P. Woodruff , Jason 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

Constructing a spanning tree of a graph is one of the most basic tasks in graph theory. We consider a relaxed version of this problem in the setting of local algorithms. The relaxation is that the constructed subgraph is a sparse spanning…

Data Structures and Algorithms · Computer Science 2021-04-28 Reut Levi , Dana Ron , Ronitt Rubinfeld

We consider the classical Minimum Balanced Cut problem: given a graph $G$, compute a partition of its vertices into two subsets of roughly equal volume, while minimizing the number of edges connecting the subsets. We present the first {\em…

Data Structures and Algorithms · Computer Science 2020-05-05 Julia Chuzhoy , Yu Gao , Jason Li , Danupon Nanongkai , Richard Peng , Thatchaphol Saranurak

We present a polynomial-time $(\alpha_{GW} + \varepsilon)$-approximation algorithm for the Maximum Cut problem on interval graphs and split graphs, where $\alpha_{GW} \approx 0.878$ is the approximation guarantee of the Goemans-Williamson…

Data Structures and Algorithms · Computer Science 2025-07-15 Jungho Ahn , Ian DeHaan , Eun Jung Kim , Euiwoong Lee

We present a general method of designing fast approximation algorithms for cut-based minimization problems in undirected graphs. In particular, we develop a technique that given any such problem that can be approximated quickly on trees,…

Data Structures and Algorithms · Computer Science 2010-11-09 Aleksander Madry

Kolla and Tulsiani [KT07,Kolla11} and Arora, Barak and Steurer [ABS10] introduced the technique of subspace enumeration, which gives approximation algorithms for graph problems such as unique games and small set expansion; the running time…

Data Structures and Algorithms · Computer Science 2012-12-11 Shayan Oveis Gharan , Luca Trevisan

The sparsest cut problem consists of identifying a small set of edges that breaks the graph into balanced sets of vertices. The normalized cut problem balances the total degree, instead of the size, of the resulting sets. Applications of…

Social and Information Networks · Computer Science 2017-02-17 Arlei Silva , Ambuj Singh , Ananthram Swami