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In a seminal paper, Erdos and Renyi identified the threshold for connectivity of the random graph G(n,p). In particular, they showed that if p >> log(n)/n then G(n,p) is almost always connected, and if p << log(n)/n then G(n,p) is almost…

Combinatorics · Mathematics 2010-09-23 Matthew Kahle

If a vertex $v$ in a graph $G$ has degree larger than the average of the degrees of its neighbors, we call it a groupie in $G$. In the current work, we study the behavior of groupie in random multipartite graphs with the link probability…

Combinatorics · Mathematics 2012-09-18 Marius Portmann , Hongyun Wang

We present a detailed study of the evolution of the number of connected components in sub-critical multiplicative random graph processes. We consider a model where edges appear independently after an exponential time at rate equal to the…

Probability · Mathematics 2026-05-19 Josué Corujo

An $(n,m)$-graph is a graph with $n$ types of arcs and $m$ types of edges. A homomorphism of an $(n,m)$-graph $G$ to another $(n,m)$-graph $H$ is a vertex mapping that preserves the adjacencies along with their types and directions. The…

Combinatorics · Mathematics 2023-10-17 Soumen Nandi , Sagnik Sen , S Taruni

We resolve a number of long-standing open problems in online graph coloring. More specifically, we develop tight lower bounds on the performance of online algorithms for fundamental graph classes. An important contribution is that our…

Data Structures and Algorithms · Computer Science 2017-07-04 Susanne Albers , Sebastian Schraink

Graph parameters such as the clique number, the chromatic number, and the independence number are central in many areas, ranging from computer networks to linguistics to computational neuroscience to social networks. In particular, the…

Computational Complexity · Computer Science 2020-12-15 Fabian Frei , Edith Hemaspaandra , Jörg Rothe

Amit and Linial showed that a random lift of a graph with minimum degree $\delta\ge3$ is asymptotically almost surely $\delta$-connected, and mentioned the problem of estimating this probability as a function of the degree of the lift. We…

Discrete Mathematics · Computer Science 2017-03-23 Shashwat Silas

In this work, we consider the problem of sampling a $k$-clique in a graph from an almost uniform distribution in sublinear time in the general graph query model. Specifically the algorithm should output each $k$-clique with probability…

Data Structures and Algorithms · Computer Science 2020-12-09 Talya Eden , Dana Ron , Will Rosenbaum

We present deterministic constant-round protocols for the graph connectivity problem in the model where each of the $n$ nodes of a graph receives a row of the adjacency matrix, and broadcasts a single sublinear size message to all other…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-06-13 Pedro Montealegre , Ioan Todinca

We investigate the joint distribution of the vertex degrees in three models of random bipartite graphs. Namely, we can choose each edge with a specified probability, choose a specified number of edges, or specify the vertex degrees in one…

Combinatorics · Mathematics 2022-12-22 Brendan D. McKay , Fiona Skerman

Given positive integers $n\ge 2k$, the {\it Kneser graph} $KG_{n,k}$ is a graph whose vertex set is the collection of all $k$-element subsets of the set $\{1,\ldots, n\}$, with edges connecting pairs of disjoint sets. One of the classical…

Combinatorics · Mathematics 2021-07-20 Sergei Kiselev , Andrey Kupavskii

This paper introduces a natural generalization of the classical edge coloring problem in graphs that provides a useful abstraction for two well-known problems in multicast switching. We show that the problem is NP-hard and evaluate the…

Data Structures and Algorithms · Computer Science 2015-12-31 Jonathan Turner

We present a distributed randomized algorithm finding Minimum Spanning Tree (MST) of a given graph in O(1) rounds, with high probability, in the Congested Clique model. The input graph in the Congested Clique model is a graph of n nodes,…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-11-01 Tomasz Jurdzinski , Krzysztof Nowicki

We study the paintability, an on-line version of choosability, of complete multipartite graphs. We do this by considering an equivalent chip game introduced by Duraj, Gutowski, and Kozik. We consider complete multipartite graphs with $ n $…

We provide a simple new randomized contraction approach to the global minimum cut problem for simple undirected graphs. The contractions exploit 2-out edge sampling from each vertex rather than the standard uniform edge sampling. We…

Data Structures and Algorithms · Computer Science 2019-09-04 Mohsen Ghaffari , Krzysztof Nowicki , Mikkel Thorup

We study Plurality Consensus in the Gossip Model over a network of $n$ anonymous agents. Each agent supports an initial opinion or color. We assume that at the onset, the number of agents supporting the plurality color exceeds that of the…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-07-11 L. Becchetti , A. Clementi , E. Natale , F. Pasquale , R. Silvestri

Consider the following random process: The vertices of a binomial random graph $G_{n,p}$ are revealed one by one, and at each step only the edges induced by the already revealed vertices are visible. Our goal is to assign to each vertex one…

Combinatorics · Mathematics 2018-02-16 Torsten Mütze , Thomas Rast , Reto Spöhel

We study the communication complexity of the Minimum Vertex Cover (MVC) problem on general graphs within the \(k\)-party one-way communication model. Edges of an arbitrary \(n\)-vertex graph are distributed among \(k\) parties. The…

Computational Complexity · Computer Science 2025-05-13 Mahsa Derakhshan , Andisheh Ghasemi , Rajmohan Rajaraman

In this paper, we study two problems related to planar matchings in random bipartite graphs. First, we colour each edge of the complete bipartite graph $K_{n,n}$ uniformly randomly from amongst ${r}$ colours and show that if ${r}$ grows…

Probability · Mathematics 2023-01-13 Ghurumuruhan Ganesan

Desirable random graph models (RGMs) should (i) reproduce common patterns in real-world graphs (e.g., power-law degrees, small diameters, and high clustering), (ii) generate variable (i.e., not overly similar) graphs, and (iii) remain…

Machine Learning · Computer Science 2025-09-26 Fanchen Bu , Ruochen Yang , Paul Bogdan , Kijung Shin