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We give a deterministic algorithm for computing a global minimum vertex cut in a vertex-weighted graph $n$ vertices and $m$ edges in $\widehat O(mn)$ time. This breaks the long-standing $\widehat \Omega(n^{4})$-time barrier in dense graphs,…

Data Structures and Algorithms · Computer Science 2025-03-28 Yonggang Jiang , Chaitanya Nalam , Thatchaphol Saranurak , Sorrachai Yingchareonthawornchai

We introduce a model for a growing random graph based on simultaneous reproduction of the vertices. The model can be thought of as a generalisation of the reproducing graphs of Southwell and Cannings and Bonato et al to allow for a random…

Probability · Mathematics 2011-04-20 Jonathan Jordan

We present an $O(n^5)$ algorithm that computes a maximum stable set of any perfect graph with no balanced skew-partition. We present $O(n^7)$ time algorithm that colors them.

Discrete Mathematics · Computer Science 2020-12-01 Maria Chudnovsky , Nicolas Trotignon , Théophile Trunck , Kristina Vuskovic

Hyperbolic random graphs (HRG) and geometric inhomogeneous random graphs (GIRG) are two similar generative network models that were designed to resemble complex real world networks. In particular, they have a power-law degree distribution…

Data Structures and Algorithms · Computer Science 2019-08-26 Thomas Bläsius , Tobias Friedrich , Maximilian Katzmann , Ulrich Meyer , Manuel Penschuck , Christopher Weyand

Reducing the running time of graph algorithms is vital for tackling real-world problems such as shortest paths and matching in large-scale graphs, where path information plays a crucial role. To address this critical challenge, this paper…

Data Structures and Algorithms · Computer Science 2026-04-14 Akshar Chavan , Sanaz Rabinia , Daniel Grosu , Marco Brocanelli

We study algorithms for spectral graph sparsification. The input is a graph $G$ with $n$ vertices and $m$ edges, and the output is a sparse graph $\tilde{G}$ that approximates $G$ in an algebraic sense. Concretely, for all vectors $x$ and…

Data Structures and Algorithms · Computer Science 2013-11-19 Ioannis Koutis , Alex Levin , Richard Peng

We study a number of graph exploration problems in the following natural scenario: an algorithm starts exploring an undirected graph from some seed node; the algorithm, for an arbitrary node $v$ that it is aware of, can ask an oracle to…

Data Structures and Algorithms · Computer Science 2017-10-25 Flavio Chierichetti , Shahrzad Haddadan

Graph generation with Machine Learning is an open problem with applications in various research fields. In this work, we propose to cast the generative process of a graph into a sequential one, relying on a node ordering procedure. We use…

Machine Learning · Statistics 2020-04-24 Davide Bacciu , Alessio Micheli , Marco Podda

A dynamic graph algorithm is a data structure that answers queries about a property of the current graph while supporting graph modifications such as edge insertions and deletions. Prior work has shown strong conditional lower bounds for…

Data Structures and Algorithms · Computer Science 2023-01-30 Monika Henzinger , Ami Paz , A. R. Sricharan

Estimating the average degree of graph is a classic problem in sublinear graph algorithm. Eden, Ron, and Seshadhri (ICALP 2017, SIDMA 2019) gave a simple algorithm for this problem whose running time depended on the graph arboricity, but…

Data Structures and Algorithms · Computer Science 2026-03-11 Talya Eden , C. Seshadhri

Vizing's theorem states that any $n$-vertex $m$-edge graph of maximum degree $\Delta$ can be edge colored using at most $\Delta + 1$ different colors [Vizing, 1964]. Vizing's original proof is algorithmic and shows that such an edge…

Data Structures and Algorithms · Computer Science 2025-10-15 Sepehr Assadi , Soheil Behnezhad , Sayan Bhattacharya , Martín Costa , Shay Solomon , Tianyi Zhang

We propose a fast approximate algorithm for large graph matching. A new projected fixed-point method is defined and a new doubly stochastic projection is adopted to derive the algorithm. Previous graph matching algorithms suffer from high…

Computer Vision and Pattern Recognition · Computer Science 2012-08-13 Yao Lu , Kaizhu Huang , Cheng-Lin Liu

This paper presents a linear prioritized local algorithm that computes large independent sets on a random $d$-regular graph with small and fixed degree $d$. We studied experimentally the independence ratio obtained by the algorithm when $ d…

Data Structures and Algorithms · Computer Science 2021-08-18 Raffaele Marino , Scott Kirkpatrick

Graph coloring is one of the central problems in distributed graph algorithms. Much of the research on this topic has focused on coloring with $\Delta+1$ colors, where $\Delta$ denotes the maximum degree. Using $\Delta+1$ colors may be…

Data Structures and Algorithms · Computer Science 2017-08-24 Mohsen Ghaffari , Christiana Lymouri

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

It was experimentally observed that the majority of real-world networks follow power law degree distribution. The aim of this paper is to study the algorithmic complexity of such "typical" networks. The contribution of this work is twofold.…

Data Structures and Algorithms · Computer Science 2015-07-10 Paweł Brach , Marek Cygan , Jakub Łącki , Piotr Sankowski

An identifying code of a graph is a dominating set which uniquely determines all the vertices by their neighborhood within the code. Whereas graphs with large minimum degree have small domination number, this is not the case for the…

Combinatorics · Mathematics 2017-01-02 Florent Foucaud , Guillem Perarnau , Oriol Serra

In this paper we focus on the problem of the degree sequence for the following random graph process. At any time-step $t$, one of the following three substeps is executed: with probability $\alpha_1$, a new vertex $x_t$ and $m$ edges…

Probability · Mathematics 2008-07-01 Xian-Yuan Wu , Zhao Dong , Ke Liu , Kai-Yuan Cai

Finding maximum-weight independent sets in graphs is an important NP-hard optimization problem. Given a vertex-weighted graph $G$, the task is to find a subset of pairwise non-adjacent vertices of $G$ with maximum weight. Most recently…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-16 Jannick Borowitz , Ernestine Großmann , Mattthias Schimek

In this paper, we study the problem of recovering the latent vertex correspondence between two correlated random graphs with vastly inhomogeneous and unknown edge probabilities between different pairs of vertices. Inspired by and extending…

Data Structures and Algorithms · Computer Science 2025-08-19 Jian Ding , Yumou Fei , Yuanzheng Wang
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