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Related papers: Towards a better approximation for sparsest cut?

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Graph signal processing (GSP) provides a powerful framework for analyzing signals arising in a variety of domains. In many applications of GSP, multiple network structures are available, each of which captures different aspects of the same…

Machine Learning · Statistics 2021-11-03 Michael Weylandt , George Michailidis , T. Mitchell Roddenberry

The minimum cut problem for an undirected edge-weighted graph asks us to divide its set of nodes into two blocks while minimizing the weight sum of the cut edges. Here, we introduce a linear-time algorithm to compute near-minimum cuts. Our…

Data Structures and Algorithms · Computer Science 2019-06-05 Monika Henzinger , Alexander Noe , Christian Schulz , Darren Strash

Analyzing the mixing time of random walks is a well-studied problem with applications in random sampling and more recently in graph partitioning. In this work, we present new analysis of random walks and evolving sets using more…

Data Structures and Algorithms · Computer Science 2015-07-09 Siu On Chan , Tsz Chiu Kwok , Lap Chi Lau

In the $k$-Cut problem, we are given an edge-weighted graph $G$ and an integer $k$, and have to remove a set of edges with minimum total weight so that $G$ has at least $k$ connected components. Prior work on this problem gives, for all $h…

Data Structures and Algorithms · Computer Science 2017-10-25 Anupam Gupta , Euiwoong Lee , Jason Li

This paper is devoted to the distributed complexity of finding an approximation of the maximum cut in graphs. A classical algorithm consists in letting each vertex choose its side of the cut uniformly at random. This does not require any…

Combinatorics · Mathematics 2021-07-08 Étienne Bamas , Louis Esperet

$ \newcommand{\kalg}{{k_{\mathrm{alg}}}} \newcommand{\kopt}{{k_{\mathrm{opt}}}} \newcommand{\algset}{{T}} \renewcommand{\Re}{\mathbb{R}} \newcommand{\eps}{\varepsilon} \newcommand{\pth}[2][\!]{#1\left({#2}\right)} \newcommand{\npoints}{n}…

Computational Geometry · Computer Science 2017-07-04 Avrim Blum , Sariel Har-Peled , Benjamin Raichel

In the decremental single-source shortest paths (SSSP) problem, the input is an undirected graph $G=(V,E)$ with $n$ vertices and $m$ edges undergoing edge deletions, together with a fixed source vertex $s\in V$. The goal is to maintain a…

Data Structures and Algorithms · Computer Science 2020-09-21 Julia Chuzhoy , Thatchaphol Saranurak

The Restricted Shortest Path (RSP) problem, also known as the Delay-Constrained Least-Cost (DCLC) problem, is an NP-hard bicriteria optimization problem on graphs with $n$ vertices and $m$ edges. In a graph where each edge is assigned a…

Data Structures and Algorithms · Computer Science 2019-11-05 David Holzmüller

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

Let $G = (V,E,w)$ be a weighted undirected graph on $|V| = n$ vertices and $|E| = m$ edges, let $k \ge 1$ be any integer, and let $\epsilon < 1$ be any parameter. We present the following results on fast constructions of spanners with…

Data Structures and Algorithms · Computer Science 2021-08-03 Hung Le , Shay Solomon

Cheeger's fundamental inequality states that any edge-weighted graph has a vertex subset $S$ such that its expansion (a.k.a. conductance) is bounded as follows: \[ \phi(S) \defeq \frac{w(S,\bar{S})}{\min \set{w(S), w(\bar{S})}} \leq…

Data Structures and Algorithms · Computer Science 2015-03-19 Anand Louis , Prasad Raghavendra , Prasad Tetali , Santosh Vempala

The All-Pairs Shortest Paths (APSP) is a foundational problem in theoretical computer science. Approximating APSP in undirected unweighted graphs has been studied for many years, beginning with the work of Dor, Halperin and Zwick…

Data Structures and Algorithms · Computer Science 2025-11-10 Ce Jin , Yael Kirkpatrick , Michał Stawarz , Virginia Vassilevska Williams

We consider the graph $k$-partitioning problem under the min-max objective, termed as Minmax $k$-cut. The input here is a graph $G=(V,E)$ with non-negative edge weights $w:E\rightarrow \mathbb{R}_+$ and an integer $k\geq 2$ and the goal is…

Data Structures and Algorithms · Computer Science 2020-11-09 Karthekeyan Chandrasekaran , Weihang Wang

In recent years, hypergraph generalizations of many graph cut problems have been introduced and analyzed as a way to better explore and understand complex systems and datasets characterized by multiway relationships. Recent work has made…

Data Structures and Algorithms · Computer Science 2021-07-05 Austin R. Benson , Jon Kleinberg , Nate Veldt

In the Max-Cut problem in the streaming model, an algorithm is given the edges of an unknown graph $G = (V,E)$ in some fixed order, and its goal is to approximate the size of the largest cut in $G$. Improving upon an earlier result of…

Data Structures and Algorithms · Computer Science 2025-09-08 Yumou Fei , Dor Minzer , Shuo Wang

The Max-Cut problem is known to be NP-hard on general graphs, while it can be solved in polynomial time on planar graphs. In this paper, we present a fixed-parameter tractable algorithm for the problem on `almost' planar graphs: Given an…

Data Structures and Algorithms · Computer Science 2019-05-27 Yasuaki Kobayashi , Yusuke Kobayashi , Shuichi Miyazaki , Suguru Tamaki

The emerging theory of graph limits exhibits an analytic perspective on graphs, showing that many important concepts and tools in graph theory and its applications can be described more naturally (and sometimes proved more easily) in…

Combinatorics · Mathematics 2023-08-01 Omri Ben-Eliezer , Eldar Fischer , Amit Levi , Yuichi Yoshida

Given a subset S of vertices of an undirected graph G, the cut-improvement problem asks us to find a subset S that is similar to A but has smaller conductance. A very elegant algorithm for this problem has been given by Andersen and Lang…

Data Structures and Algorithms · Computer Science 2014-11-07 Lorenzo Orecchia , Zeyuan Allen Zhu

In this short paper, we present an improved algorithm for approximating the minimum cut on distributed (CONGEST) networks. Let $\lambda$ be the minimum cut. Our algorithm can compute $\lambda$ exactly in…

Data Structures and Algorithms · Computer Science 2014-05-16 Danupon Nanongkai

The vertex expansion of the graph is a fundamental graph parameter. Given a graph $G=(V,E)$ and a parameter $\delta \in (0,1/2]$, its $\delta$-Small-Set Vertex Expansion (SSVE) is defined as \[ \min_{S : |S| = \delta |V|}…

Data Structures and Algorithms · Computer Science 2023-11-29 Suprovat Ghoshal , Anand Louis