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Related papers: Cheeger-type approximation for sparsest $st$-cut

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In this paper, assuming the low-degree conjecture, we provide evidence of computational hardness for two problems: (1) the (partial) matching recovery problem in the sparse correlated Erd\H{o}s-R\'enyi graphs $\mathcal G(n,q;\rho)$ when the…

Machine Learning · Statistics 2025-12-30 Zhangsong Li

We consider the classical minimum and maximum cut problems: find a partition of vertices of a graph into two disjoint subsets that minimize or maximize the sum of the weights of edges with endpoints in different subsets. It is known that if…

Combinatorics · Mathematics 2024-02-20 Andrei V. Nikolaev , Alexander V. Korostil

Graph compression or sparsification is a basic information-theoretic and computational question. A major open problem in this research area is whether $(1+\epsilon)$-approximate cut-preserving vertex sparsifiers with size close to the…

Data Structures and Algorithms · Computer Science 2020-07-16 Parinya Chalermsook , Syamantak Das , Bundit Laekhanukit , Yunbum Kook , Yang P. Liu , Richard Peng , Mark Sellke , Daniel Vaz

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

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

Partition problems in graphs are extremely important in applications, as shown in the Data science and Machine learning literature. One approach is spectral partitioning based on a Fiedler vector, i.e., an eigenvector corresponding to the…

Combinatorics · Mathematics 2023-06-23 Enide Andrade , Geir Dahl

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

Given an edge-weighted graph, how many minimum $k$-cuts can it have? This is a fundamental question in the intersection of algorithms, extremal combinatorics, and graph theory. It is particularly interesting in that the best known bounds…

Data Structures and Algorithms · Computer Science 2019-06-04 Anupam Gupta , Euiwoong Lee , Jason Li

We develop a new technique for constructing sparse graphs that allow us to prove near-linear lower bounds on the round complexity of computing distances in the CONGEST model. Specifically, we show an $\widetilde{\Omega}(n)$ lower bound for…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-05-18 Amir Abboud , Keren Censor-Hillel , Seri Khoury

This paper treats the problem of minimizing a general continuously differentiable function subject to sparsity constraints. We present and analyze several different optimality criteria which are based on the notions of stationarity and…

Information Theory · Computer Science 2012-03-22 Amir Beck , Yonina C. Eldar

We establish that a simple polynomial-time algorithm that we call reweighted spectral partitioning obtains small 2/3-balanced vertex-separators for a number of graph classes, including $O(\sqrt{n})$-sized separators for planar graphs,…

Data Structures and Algorithms · Computer Science 2025-11-18 Jack Spalding-Jamieson

The {\sc $c$-Balanced Separator} problem is a graph-partitioning problem in which given a graph $G$, one aims to find a cut of minimum size such that both the sides of the cut have at least $cn$ vertices. In this paper, we present new…

Data Structures and Algorithms · Computer Science 2010-11-22 Manjish Pal

Consider the following "local" cut-detection problem in a directed graph: We are given a starting vertex $s$ and need to detect whether there is a cut with at most $k$ edges crossing the cut such that the side of the cut containing $s$ has…

Data Structures and Algorithms · Computer Science 2019-04-23 Sebastian Forster , Liu Yang

The seminal work of Bencz\'ur and Karger demonstrated cut sparsifiers of near-linear size. Subsequent extensions have yielded sparsifiers for hypergraph cuts and more recently linear codes over Abelian groups. A decade ago, Kogan and…

Data Structures and Algorithms · Computer Science 2026-05-19 Joshua Brakensiek , Venkatesan Guruswami

Graph-based nearest neighbor search methods have seen a surge of popularity in recent years, offering state-of-the-art performance across a wide variety of applications. Central to these methods is the task of constructing a sparse…

Data Structures and Algorithms · Computer Science 2025-10-24 Alex Conway , Laxman Dhulipala , Martin Farach-Colton , Rob Johnson , Ben Landrum , Christopher Musco , Yarin Shechter , Torsten Suel , Richard Wen

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

Given a graph $G$ cellularly embedded on a surface $\Sigma$ of genus $g$, a cut graph is a subgraph of $G$ such that cutting $\Sigma$ along $G$ yields a topological disk. We provide a fixed parameter tractable approximation scheme for the…

Data Structures and Algorithms · Computer Science 2015-07-08 Vincent Cohen-Addad , Arnaud de Mesmay

Let M be a bounded domain of a Euclidian space with smooth boundary. We relate the Cheeger constant of M and the conductance of a neighborhood graph defined on a random sample from M. By restricting the minimization defining the latter over…

Statistics Theory · Mathematics 2013-03-05 Ery Arias-Castro , Bruno Pelletier , Pierre Pudlo

We present the first near-linear work and poly-logarithmic depth algorithm for computing a minimum cut in a graph, while previous parallel algorithms with poly-logarithmic depth required at least quadratic work in the number of vertices. In…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-07-03 Barbara Geissmann , Lukas Gianinazzi

Coresets have become an invaluable tool for solving $k$-means and kernel $k$-means clustering problems on large datasets with small numbers of clusters. On the other hand, spectral clustering works well on sparse graphs and has recently…

Machine Learning · Computer Science 2025-03-11 Ben Jourdan , Gregory Schwartzman , Peter Macgregor , He Sun