English
Related papers

Related papers: Near-linear Size Hypergraph Cut Sparsifiers

200 papers

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

We prove that every graph has a spectral sparsifier with a number of edges linear in its number of vertices. As linear-sized spectral sparsifiers of complete graphs are expanders, our sparsifiers of arbitrary graphs can be viewed as…

Data Structures and Algorithms · Computer Science 2024-06-01 Joshua Batson , Daniel A. Spielman , Nikhil Srivastava

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 2014-09-09 Michael Kapralov , Sanjeev Khanna , Madhu Sudan

We give a deterministic, nearly logarithmic-space algorithm for mild spectral sparsification of undirected graphs. Given a weighted, undirected graph $G$ on $n$ vertices described by a binary string of length $N$, an integer $k\leq \log n$,…

Data Structures and Algorithms · Computer Science 2020-04-21 Dean Doron , Jack Murtagh , Salil Vadhan , David Zuckerman

The expansion of a hypergraph, a natural extension of the notion of expansion in graphs, is defined as the minimum over all cuts in the hypergraph of the ratio of the number of the hyperedges cut to the size of the smaller side of the cut.…

Data Structures and Algorithms · Computer Science 2014-04-18 Anand Louis , Yury Makarychev

The hypergraph minimum cut problem aims to partition its vertices into two blocks while minimizing the total weight of the cut hyperedges. This fundamental problem arises in network reliability, VLSI design, and community detection. We…

Data Structures and Algorithms · Computer Science 2025-05-01 Adil Chhabra , Christian Schulz , Bora Uçar , Loris Wilwert

We design new algorithms for approximating 2CSPs on graphs with bounded threshold rank, that is, whose normalized adjacency matrix has few eigenvalues larger than $\varepsilon$, smaller than $-\varepsilon$, or both. Unlike on worst-case…

Data Structures and Algorithms · Computer Science 2025-11-17 Prashanti Anderson , Samuel B. Hopkins , Amit Rajaraman , David Steurer

The branchwidth of a graph has been introduced by Roberson and Seymour as a measure of the tree-decomposability of a graph, alternative to treewidth. Branchwidth is polynomially computable on planar graphs by the celebrated ``Ratcatcher''…

Combinatorics · Mathematics 2026-01-29 Dimitrios M. Thilikos , Sebastian Wiederrecht

An instance of the Connected Maximum Cut problem consists of an undirected graph G = (V, E) and the goal is to find a subset of vertices S $\subseteq$ V that maximizes the number of edges in the cut \delta(S) such that the induced graph…

Data Structures and Algorithms · Computer Science 2015-07-03 MohammadTaghi Hajiaghayi , Guy Kortsarz , Robert MacDavid , Manish Purohit , Kanthi Sarpatwar

Recently [Bhattacharya et al., STOC 2015] provide the first non-trivial algorithm for the densest subgraph problem in the streaming model with additions and deletions to its edges, i.e., for dynamic graph streams. They present a…

Data Structures and Algorithms · Computer Science 2015-07-30 Hossein Esfandiari , MohammadTaghi Hajiaghayi , David P. Woodruff

We provide an algorithm that, given an $n$-vertex $m$-edge Eulerian graph with polynomially bounded weights, computes an $\breve{O}(n\log^{2} n \cdot \varepsilon^{-2})$-edge $\varepsilon$-approximate Eulerian sparsifier with high…

Data Structures and Algorithms · Computer Science 2024-08-20 Arun Jambulapati , Sushant Sachdeva , Aaron Sidford , Kevin Tian , Yibin Zhao

Graph sketching has emerged as a powerful technique for processing massive graphs that change over time (i.e., are presented as a dynamic stream of edge updates) over the past few years, starting with the work of Ahn, Guha and McGregor…

Data Structures and Algorithms · Computer Science 2019-03-29 Michael Kapralov , Aida Mousavifar , Cameron Musco , Christopher Musco , Navid Nouri

We present the first single pass algorithm for computing spectral sparsifiers of graphs in the dynamic semi-streaming model. Given a single pass over a stream containing insertions and deletions of edges to a graph G, our algorithm…

Data Structures and Algorithms · Computer Science 2015-04-17 Michael Kapralov , Yin Tat Lee , Cameron Musco , Christopher Musco , Aaron Sidford

The attention mechanism has demonstrated superior performance for inference over nodes in graph neural networks (GNNs), however, they result in a high computational burden during both training and inference. We propose FastGAT, a method to…

Machine Learning · Computer Science 2020-10-06 Rakshith S Srinivasa , Cao Xiao , Lucas Glass , Justin Romberg , Jimeng Sun

We address counting and optimization variants of multicriteria global min-cut and size-constrained min-$k$-cut in hypergraphs. 1. For an $r$-rank $n$-vertex hypergraph endowed with $t$ hyperedge-cost functions, we show that the number of…

Data Structures and Algorithms · Computer Science 2020-06-23 Calvin Beideman , Karthekeyan Chandrasekaran , Chao Xu

In this paper we introduce a notion of spectral approximation for directed graphs. While there are many potential ways one might define approximation for directed graphs, most of them are too strong to allow sparse approximations in…

Data Structures and Algorithms · Computer Science 2016-11-03 Michael B. Cohen , Jonathan Kelner , John Peebles , Richard Peng , Anup Rao , Aaron Sidford , Adrian Vladu

Fine-grained reductions have established equivalences between many core problems with $\tilde{O}(n^3)$-time algorithms on $n$-node weighted graphs, such as Shortest Cycle, All-Pairs Shortest Paths (APSP), Radius, Replacement Paths, Second…

Data Structures and Algorithms · Computer Science 2020-05-07 Andrea Lincoln , Virginia Vassilevska Williams , Ryan Williams

Constructing a spanning tree of a graph is one of the most basic tasks in graph theory. We consider this problem in the setting of local algorithms: one wants to quickly determine whether a given edge $e$ is in a specific spanning tree,…

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

We present a quasi linear-time algorithm for Maximum Matching on distance-hereditary graphs and some of their generalizations. This improves on [Dragan, WG'97], who proposed such an algorithm for the subclass of (tent,hexahedron)-free…

Data Structures and Algorithms · Computer Science 2018-04-26 Guillaume Ducoffe , Alexandru Popa

Despite there being significant work on developing spectral, and metric embedding based approximation algorithms for hypergraph generalizations of conductance, little is known regarding the approximability of hypergraph partitioning…

Data Structures and Algorithms · Computer Science 2023-07-27 Antares Chen , Lorenzo Orecchia , Erasmo Tani