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Answering a question of Erd\H{o}s and Ne\v{s}et\v{r}il, we show that the maximum number of inclusion-wise minimal vertex cuts in a graph on $n$ vertices is at most $1.8899^n$ for large enough $n$.

Combinatorics · Mathematics 2024-09-06 Domagoj Bradač

We analyse the scaling limit of the sizes of the largest components of the Random Intersection Graph $G(n,m,p)$ close to the critical point $p=\frac{1}{\sqrt{nm}}$, when the numbers $n$ of individuals and $m$ of communities have different…

Probability · Mathematics 2019-10-30 Lorenzo Federico

The presence of a random magnetic field in ferromagnetic systems leads, in the broken phase, to an anomalous $O(\sqrt{1/N})$ convergence of some thermodynamic quantities to their asymptotic limits. Here we show a general method, based on…

Disordered Systems and Neural Networks · Physics 2014-10-16 Carlo Lucibello , Flaviano Morone , Giorgio Parisi , Federico Ricci-Tersenghi , Tommaso Rizzo

In this note, we revisit the recursive random contraction algorithm of Karger and Stein for finding a minimum cut in a graph. Our revisit is occasioned by a paper of Fox, Panigrahi, and Zhang which gives an extension of the Karger-Stein…

Data Structures and Algorithms · Computer Science 2020-10-30 David R. Karger , David P. Williamson

We study a variant of the Erd\H{o}s Matching Problem in random hypergraphs. Let $\mathcal{K}_p(n,k)$ denote the Erd\H{o}s-R\'enyi random $k$-uniform hypergraph on $n$ vertices where each possible edge is included with probability $p$. We…

Combinatorics · Mathematics 2025-09-24 Peter Frankl , Jiaxi Nie , Jian Wang

Erd\H{o}s posed the problem of finding conditions on a graph $G$ that imply the largest number of edges in a triangle-free subgraph is equal to the largest number of edges in a bipartite subgraph. We generalize this problem to general…

Combinatorics · Mathematics 2021-02-03 Bingchen Qian , Chengfei Xie , Gennian Ge

The Sparsest Cut is a fundamental optimization problem that has been extensively studied. For planar inputs the problem is in $P$ and can be solved in $\tilde{O}(n^3)$ time if all vertex weights are $1$. Despite a significant amount of…

Data Structures and Algorithms · Computer Science 2020-07-07 Amir Abboud , Vincent Cohen-Addad , Philip N. Klein

We consider a non-projective class of inhomogeneous random graph models with interpretable parameters and a number of interesting asymptotic properties. Using the results of Bollob\'as et al. [2007], we show that i) the class of models is…

Machine Learning · Statistics 2018-10-04 Juho Lee , Lancelot F. James , Seungjin Choi , François Caron

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

For two correlated graphs which are independently sub-sampled from a common Erd\H{o}s-R\'enyi graph $\mathbf{G}(n, p)$, we wish to recover their \emph{latent} vertex matching from the observation of these two graphs \emph{without labels}.…

Statistics Theory · Mathematics 2022-05-31 Jian Ding , Hang Du

We consider ferromagnetic Ising models on graphs that converge locally to trees. Examples include random regular graphs with bounded degree and uniformly random graphs with bounded average degree. We prove that the "cavity" prediction for…

Probability · Mathematics 2016-09-08 Amir Dembo , Andrea Montanari

Spectral hypergraph sparsification, an attempt to extend well-known spectral graph sparsification to hypergraphs, has been extensively studied over the past few years. For undirected hypergraphs, Kapralov, Krauthgamer, Tardos, and…

Data Structures and Algorithms · Computer Science 2023-05-12 Kazusato Oko , Shinsaku Sakaue , Shin-ichi Tanigawa

Let $\Xi$ be the adjacency matrix of an Erd\H{o}s-R\'enyi graph on $n$ vertices and with parameter $p$ and consider $A$ a $n\times n$ centered random symmetric matrix with bounded i.i.d. entries above the diagonal. When the mean degree $np$…

Probability · Mathematics 2024-01-23 Fanny Augeri

For graphs $G$ and $H$, let $G {\displaystyle\smash{\begin{subarray}{c} \hbox{$\tiny\rm rb$} \\ \longrightarrow \\ \hbox{$\tiny\rm p$} \end{subarray}}}H$ denote the property that for every proper edge-colouring of $G$ there is a rainbow $H$…

Combinatorics · Mathematics 2023-01-20 Yoshiharu Kohayakawa , Guilherme Oliveira Mota , Olaf Parczyk , Jakob Schnitzer

A bisection in a graph is a cut in which the number of vertices in the two parts differ by at most 1. In this paper, we give lower bounds for the maximum weight of bisections of edge-weighted graphs with bounded maximum degree. Our results…

Combinatorics · Mathematics 2024-01-23 Stefanie Gerke , Gregory Gutin , Anders Yeo , Yacong Zhou

The distribution $\mathsf{RGG}(n,\mathbb{S}^{d-1},p)$ is formed by sampling independent vectors $\{V_i\}_{i = 1}^n$ uniformly on $\mathbb{S}^{d-1}$ and placing an edge between pairs of vertices $i$ and $j$ for which $\langle V_i,V_j\rangle…

Probability · Mathematics 2024-08-05 Kiril Bangachev , Guy Bresler

We show that in random $K$-uniform hypergraphs of constant average degree, for even $K \geq 4$, local algorithms defined as factors of i.i.d. can not find nearly maximal cuts, when the average degree is sufficiently large. These algorithms…

Probability · Mathematics 2019-11-05 Wei-Kuo Chen , David Gamarnik , Dmitry Panchenko , Mustazee Rahman

Random graph alignment refers to recovering the underlying vertex correspondence between two random graphs with correlated edges. This can be viewed as an average-case and noisy version of the well-known graph isomorphism problem. For the…

Machine Learning · Statistics 2021-08-18 Luca Ganassali , Laurent Massoulié , Marc Lelarge

In this note, we describe a $\alpha_{GW} + \tilde{\Omega}(1/d^2)$-factor approximation algorithm for Max-Cut on weighted graphs of degree $\leq d$. Here, $\alpha_{GW}\approx 0.878$ is the worst-case approximation ratio of the…

Data Structures and Algorithms · Computer Science 2022-06-23 Jun-Ting Hsieh , Pravesh K. Kothari

The on-line nearest-neighbour graph on a sequence of $n$ uniform random points in $(0,1)^d$ ($d \in \N$) joins each point after the first to its nearest neighbour amongst its predecessors. For the total power-weighted edge-length of this…

Probability · Mathematics 2009-05-07 Andrew R. Wade
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