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The Kadison-Singer Conjecture, as proved by Marcus, Spielman, and Srivastava (MSS) [Ann. Math. 182, 327-350 (2015)], has been informally thought of as a strengthening of Batson, Spielman, and Srivastava's theorem that every undirected graph…

Data Structures and Algorithms · Computer Science 2024-01-09 Phevos Paschalidis , Ashley Zhuang

The Marcus-Spielman-Srivastava theorem (Annals of Mathematics, 2015) for the Kadison-Singer conjecture implies the following result in spectral graph theory: For any undirected graph $G = (V,E)$ with a maximum edge effective resistance at…

Combinatorics · Mathematics 2025-09-16 Surya Teja Gavva , Peng Zhang

We study the detection and the reconstruction of a large very dense subgraph in a social graph with $n$ nodes and $m$ edges given as a stream of edges, when the graph follows a power law degree distribution, in the regime when $m=O(n. \log…

Data Structures and Algorithms · Computer Science 2023-06-22 Claire Mathieu , Michel de Rougemont

In this paper we consider the problem of embedding almost-spanning, bounded degree graphs in a random graph. In particular, let $\Delta\geq 5$, $\varepsilon > 0$ and let $H$ be a graph on $(1-\varepsilon)n$ vertices and with maximum degree…

Combinatorics · Mathematics 2017-08-04 Asaf Ferber , Kyle Luh , Oanh Nguyen

Dense subgraph discovery is an important graph-mining primitive with a variety of real-world applications. One of the most well-studied optimization problems for dense subgraph discovery is the densest subgraph problem, where given an…

Data Structures and Algorithms · Computer Science 2021-10-26 Francesco Bonchi , David García-Soriano , Atsushi Miyauchi , Charalampos E. Tsourakakis

Semi-random processes involve an adaptive decision-maker, whose goal is to achieve some predetermined objective in an online randomized environment. They have algorithmic implications in various areas of computer science, as well as…

Combinatorics · Mathematics 2020-09-29 Omri Ben-Eliezer , Lior Gishboliner , Dan Hefetz , Michael Krivelevich

Let $H_n$ be a graph on $n$ vertices and let $\ber{H_n}$ denote the complement of $H_n$. Suppose that $\Delta = \Delta(n)$ is the maximum degree of $\ber{H_n}$. We analyse three algorithms for sampling $d$-regular subgraphs ($d$-factors) of…

Combinatorics · Mathematics 2019-10-25 Pu Gao , Catherine Greenhill

Let $G=(V,E)$ be a finite graph. For $v\in V$ we denote by $G_v$ the subgraph of $G$ that is induced by $v$'s neighbor set. We say that $G$ is $(a,b)$-regular for $a>b>0$ integers, if $G$ is $a$-regular and $G_v$ is $b$-regular for every…

Combinatorics · Mathematics 2019-08-29 Michael Chapman , Nati Linial , Yuval Peled

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 prove a robust version of a graph embedding theorem of Sauer and Spencer. To state this sparser analogue, we define $G(p)$ to be a random subgraph of $G$ obtained by retaining each edge of $G$ independently with probability $p \in…

Combinatorics · Mathematics 2025-07-08 Peter Allen , Julia Böttcher , Yoshiharu Kohayakawa , Mihir Neve

A regular graph $G = (V,E)$ is an $(\varepsilon,\gamma)$ small-set expander if for any set of vertices of fractional size at most $\varepsilon$, at least $\gamma$ of the edges that are adjacent to it go outside. In this paper, we give a…

Computational Complexity · Computer Science 2022-11-18 Mark Braverman , Dor Minzer

We contribute an approach to the problem of locally computing sparse connected subgraphs of dense graphs. In this setting, given an edge in a connected graph $G = (V, E)$, an algorithm locally decides its membership in a sparse connected…

Data Structures and Algorithms · Computer Science 2020-07-13 Rogers Epstein

We study structural conditions in dense graphs that guarantee the existence of vertex-spanning substructures such as Hamilton cycles. It is easy to see that every Hamiltonian graph is connected, has a perfect fractional matching and,…

Combinatorics · Mathematics 2023-06-21 Richard Lang , Nicolás Sanhueza-Matamala

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

Dense subgraph discovery is an important primitive in graph mining, which has a wide variety of applications in diverse domains. In the densest subgraph problem, given an undirected graph $G=(V,E)$ with an edge-weight vector $w=(w_e)_{e\in…

Social and Information Networks · Computer Science 2021-10-27 Atsushi Miyauchi , Akiko Takeda

Consider a `dense' Erd\H{o}s--R\'enyi random graph model $G=G_{n,M}$ with $n$ vertices and $M$ edges, where we assume the edge density $M/\binom{n}{2}$ is bounded away from 0 and 1. Fix $k=k(n)$ with $k/n$ bounded away from 0 and~1, and let…

Combinatorics · Mathematics 2025-04-01 Paul Balister , Emil Powierski , Alex Scott , Jane Tan

A $(\phi,\epsilon)$-expander-decomposition of a graph $G$ (with $n$ vertices and $m$ edges) is a partition of $V$ into clusters $V_1,\ldots,V_k$ with conductance $\Phi(G[V_i]) \ge \phi$, such that there are at most $\epsilon m$…

Data Structures and Algorithms · Computer Science 2025-02-04 Daniel Agassy , Dani Dorfman , Haim Kaplan

Dense subgraph discovery is a fundamental problem in graph mining with a wide range of applications \cite{gionis2015dense}. Despite a large number of applications ranging from computational neuroscience to social network analysis, that take…

Social and Information Networks · Computer Science 2021-12-08 Tianyi Chen , Francesco Bonchi , David Garcia-Soriano , Atsushi Miyauchi , Charalampos E. Tsourakakis

An $(\epsilon,\phi)$-expander decomposition of a graph $G=(V,E)$ is a clustering of the vertices $V=V_{1}\cup\cdots\cup V_{x}$ such that (1) each cluster $V_{i}$ induces subgraph with conductance at least $\phi$, and (2) the number of…

Data Structures and Algorithms · Computer Science 2019-05-28 Yi-Jun Chang , Thatchaphol Saranurak

The significant progress in constructing graph spanners that are sparse (small number of edges) or light (low total weight) has skipped spanners that are everywhere-sparse (small maximum degree). This disparity is in line with other network…

Data Structures and Algorithms · Computer Science 2012-05-02 Eden Chlamtac , Michael Dinitz , Robert Krauthgamer
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