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For a graph $G$ define the parameters $\ell(G)$ and $L(G)$ as the minimum and maximum value of $\nu(G\backslash F)$, where $F$ is a maximum matching of $G$ and $\nu(G)$ is the matching number of $G$. In this paper, we show that there is a…

Combinatorics · Mathematics 2025-04-29 Vahan Mkrtchyan

One of the most useful measures of cluster quality is the modularity of a partition, which measures the difference between the number of the edges joining vertices from the same cluster and the expected number of such edges in a random…

Data Analysis, Statistics and Probability · Physics 2009-09-29 Hristo Djidjev

The method for analyzing algorithmic runtime complexity using decision trees is discussed using the sorting algorithm. This method is then extended to optimal algorithms which may find all cliques of size q in network N, or simply the first…

Computational Complexity · Computer Science 2025-05-09 Daniel Uribe

To study the question under which circumstances small solutions can be found faster than by exhaustive search (and by how much), we study the fine-grained complexity of Boolean constraint satisfaction with size constraint exactly $k$. More…

Computational Complexity · Computer Science 2020-05-26 Marvin Künnemann , Dániel Marx

The intersection graph of a collection of trapezoids with corner points lying on two parallel lines is called a trapezoid graph. These graphs and their generalizations were applied in various fields, including modeling channel routing…

Data Structures and Algorithms · Computer Science 2011-06-16 Aleksandar Ilic

We consider a variant of the planted clique problem where we are allowed unbounded computational time but can only investigate a small part of the graph by adaptive edge queries. We determine (up to logarithmic factors) the number of…

Combinatorics · Mathematics 2020-07-27 Miklós Z. Rácz , Benjamin Schiffer

We propose an efficient algorithm for graph matching based on similarity scores constructed from counting a certain family of weighted trees rooted at each vertex. For two Erd\H{o}s-R\'enyi graphs $\mathcal{G}(n,q)$ whose edges are…

Data Structures and Algorithms · Computer Science 2023-02-15 Cheng Mao , Yihong Wu , Jiaming Xu , Sophie H. Yu

We study the problem of approximating the number of $k$-cliques in a graph when given query access to the graph. We consider the standard query model for general graphs via (1) degree queries, (2) neighbor queries and (3) pair queries. Let…

Data Structures and Algorithms · Computer Science 2018-03-14 Talya Eden , Dana Ron , C. Seshadhri

It is a critical issue to compute the shortest paths between nodes in networks. Exact algorithms for shortest paths are usually inapplicable for large scale networks due to the high computational complexity. In this paper, we propose a…

Social and Information Networks · Computer Science 2015-06-29 Shi-nan Gong , Duan-bing Chen , Hui Gao , Guan-nan Wang , Liang-wei Wang

Given an undirected graph and $0\le\epsilon\le1$, a set of nodes is called $\epsilon$-near clique if all but an $\epsilon$ fraction of the pairs of nodes in the set have a link between them. In this paper we present a fast synchronous…

Distributed, Parallel, and Cluster Computing · Computer Science 2009-05-27 Zvika Brakerski , Boaz Patt-Shamir

We present a data stream algorithm for estimating the size of the maximum matching of a low arboricity graph. Recall that a graph has arboricity $\alpha$ if its edges can be partitioned into at most $\alpha$ forests and that a planar graph…

Data Structures and Algorithms · Computer Science 2017-08-15 Andrew McGregor , Sofya Vorotnikova

Finding cohesive subgraphs in a large graph has many important applications, such as community detection and biological network analysis. Clique is often a too strict cohesive structure since communities or biological modules rarely form as…

Data Structures and Algorithms · Computer Science 2024-06-11 Qihao Cheng , Da Yan , Tianhao Wu , Lyuheng Yuan , Ji Cheng , Zhongyi Huang , Yang Zhou

Simplifying graphs is a very applicable problem in numerous domains, especially in computational geometry. Given a geometric graph and a threshold, the minimum-complexity graph simplification asks for computing an alternative graph of…

Computational Geometry · Computer Science 2021-11-05 Omrit Filtser , Majid Mirzanezhad , Carola Wenk

We give an algorithm that decides whether the bipartite crossing number of a given graph is at most $k$. The running time of the algorithm is upper bounded by $2^{O(k)} + n^{O(1)}$, where $n$ is the number of vertices of the input graph,…

Data Structures and Algorithms · Computer Science 2015-12-21 Yasuaki Kobayashi , Hisao Tamaki

Treewidth is a measure of how tree-like a graph is. It has many important algorithmic applications because many NP-hard problems on general graphs become tractable when restricted to graphs of bounded treewidth. Algorithms for problems on…

Data Structures and Algorithms · Computer Science 2020-06-03 Johan M. M. van Rooij

$k$-defective cliques relax cliques by allowing up-to $k$ missing edges from being a complete graph. This relaxation enables us to find larger near-cliques and has applications in link prediction, cluster detection, social network analysis…

Data Structures and Algorithms · Computer Science 2023-09-07 Lijun Chang

Optimal decision tree (\odt) is a fundamental problem arising in applications such as active learning, entity identification, and medical diagnosis. An instance of \odt is given by $m$ hypotheses, out of which an unknown ``true'' hypothesis…

Data Structures and Algorithms · Computer Science 2025-05-22 Zhengjia Zhuo , Viswanath Nagarajan

The importance of classifying connections in large graphs has been the motivation for a rich line of work on distributed subgraph finding that has led to exciting recent breakthroughs. A crucial aspect that remained open was whether…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-09-27 Keren Censor-Hillel , Dean Leitersdorf , David Vulakh

This paper deals with the problem of finding a collection of vertex-disjoint paths in a given graph G=(V,E) such that each path has at least four vertices and the total number of vertices in these paths is maximized. The problem is NP-hard…

Data Structures and Algorithms · Computer Science 2023-04-26 Mingyang Gong , Zhi-Zhong Chen , Guohui Lin , Zhaohui Zhan

We show that, for any graph optimization problem in which the feasible solutions can be expressed by a formula in monadic second-order logic describing sets of vertices or edges and in which the goal is to minimize the sum of the weights in…

Data Structures and Algorithms · Computer Science 2017-03-09 David Eppstein , Denis Kurz
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