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We develop a new framework for generalizing approximation algorithms from the structural graph algorithm literature so that they apply to graphs somewhat close to that class (a scenario we expect is common when working with real-world…

We give an approximation algorithm for non-uniform sparsest cut with the following guarantee: For any $\epsilon,\delta \in (0,1)$, given cost and demand graphs with edge weights $C, D$ respectively, we can find a set $T\subseteq V$ with…

Data Structures and Algorithms · Computer Science 2015-03-19 Venkatesan Guruswami , Ali Kemal Sinop

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

Given a graph $G=(V,E)$ with two distinguished vertices $s,t\in V$ and an integer parameter $L>0$, an {\em $L$-bounded cut} is a subset $F$ of edges (vertices) such that the every path between $s$ and $t$ in $G\setminus F$ has length more…

Data Structures and Algorithms · Computer Science 2017-09-11 Petr Kolman

Sketching and streaming algorithms are in the forefront of current research directions for cut problems in graphs. In the streaming model, we show that $(1-\epsilon)$-approximation for Max-Cut must use $n^{1-O(\epsilon)}$ space; moreover,…

Data Structures and Algorithms · Computer Science 2026-02-23 Dmitry Kogan , Robert Krauthgamer

We consider the problem of query-efficient global max-cut on a weighted undirected graph in the value oracle model examined by [RSW18]. Graph algorithms in this cut query model and other query models have recently been studied for various…

Data Structures and Algorithms · Computer Science 2024-04-24 Orestis Plevrakis , Seyoon Ragavan , S. Matthew Weinberg

We consider the problem of estimating the value of MAX-CUT in a graph in the streaming model of computation. At one extreme, there is a trivial $2$-approximation for this problem that uses only $O(\log n)$ space, namely, count the number of…

Data Structures and Algorithms · Computer Science 2018-11-28 Michael Kapralov , Dmitry Krachun

Cut and spectral sparsification of graphs have numerous applications, including e.g. speeding up algorithms for cuts and Laplacian solvers. These powerful notions have recently been extended to hypergraphs, which are much richer and may…

Data Structures and Algorithms · Computer Science 2021-04-13 Michael Kapralov , Robert Krauthgamer , Jakab Tardos , Yuichi Yoshida

We give efficient distributed algorithms for the minimum vertex cover problem in bipartite graphs in the CONGEST model. From K\H{o}nig's theorem, it is well known that in bipartite graphs the size of a minimum vertex cover is equal to the…

Data Structures and Algorithms · Computer Science 2020-11-20 Salwa Faour , Fabian Kuhn

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

The task of finding an extension to a given partial drawing of a graph while adhering to constraints on the representation has been extensively studied in the literature, with well-known results providing efficient algorithms for…

Computational Geometry · Computer Science 2023-02-21 Sujoy Bhore , Robert Ganian , Liana Khazaliya , Fabrizio Montecchiani , Martin Nöllenburg

Expander decompositions have become one of the central frameworks in the design of fast algorithms. For an undirected graph $G=(V,E)$, a near-optimal $\phi$-expander decomposition is a partition $V_1, V_2, \ldots, V_k$ of the vertex set $V$…

Data Structures and Algorithms · Computer Science 2025-01-07 Daoyuan Chen , Simon Meierhans , Maximilian Probst Gutenberg , Thatchaphol Saranurak

For many hard computational problems, simple algorithms that run in time $2^n \cdot n^{O(1)}$ arise, say, from enumerating all subsets of a size-$n$ set. Finding (exponentially) faster algorithms is a natural goal that has driven much of…

Data Structures and Algorithms · Computer Science 2025-06-30 László Kozma , Junqi Tan

We give an algorithm to find a minimum cut in an edge-weighted directed graph with $n$ vertices and $m$ edges in $\tilde O(n\cdot \max(m^{2/3}, n))$ time. This improves on the 30 year old bound of $\tilde O(nm)$ obtained by Hao and Orlin…

Data Structures and Algorithms · Computer Science 2021-11-18 Ruoxu Cen , Jason Li , Danupon Nanongkai , Debmalya Panigrahi , Kent Quanrud , Thatchaphol Saranurak

We present an approximation scheme for optimizing certain Quadratic Integer Programming problems with positive semidefinite objective functions and global linear constraints. This framework includes well known graph problems such as Minimum…

Computational Complexity · Computer Science 2015-03-19 Venkatesan Guruswami , Ali Kemal Sinop

We give a nearly optimal sublinear-time algorithm for approximating the size of a minimum vertex cover in a graph G. The algorithm may query the degree deg(v) of any vertex v of its choice, and for each 1 <= i <= deg(v), it may ask for the…

Data Structures and Algorithms · Computer Science 2011-10-06 Krzysztof Onak , Dana Ron , Michal Rosen , Ronitt Rubinfeld

Expander graphs are known to be robust to edge deletions in the following sense: for any online sequence of edge deletions $e_1, e_2, \ldots, e_k$ to an $m$-edge graph $G$ that is initially a $\phi$-expander, the algorithm can grow a set $P…

Data Structures and Algorithms · Computer Science 2025-04-02 Simon Meierhans , Maximilian Probst Gutenberg , Thatchaphol Saranurak

A set cover of a hypergraph $H$ is a set of vertices intersecting every hyperedge. In the minimum sum set cover problem, vertices are selected one by one; each edge pays the position of the first vertex that hits it, and the objective is to…

Discrete Mathematics · Computer Science 2026-05-22 Zhongyi Zhang , Yixin Cao

Effective Resistance (ER) is a fundamental tool in various graph learning tasks. In this paper, we address the problem of efficiently approximating ER on a graph $\mathcal{G}=(\mathcal{V},\mathcal{E})$ with $n$ vertices and $m$ edges.…

Data Structures and Algorithms · Computer Science 2025-07-08 Yichun Yang , Rong-Hua Li , Meihao Liao , Guoren Wang

The radius and diameter are fundamental graph parameters. They are defined as the minimum and maximum of the eccentricities in a graph, respectively, where the eccentricity of a vertex is the largest distance from the vertex to another…

Data Structures and Algorithms · Computer Science 2015-06-08 Amir Abboud , Virginia Vassilevska Williams , Joshua Wang