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In this paper, we provide polynomial-time algorithms for different extensions of the matching counting problem, namely maximal matchings, path matchings (linear forest) and paths, on graph classes of bounded clique-width. For maximal…

Discrete Mathematics · Computer Science 2018-06-05 Benjamin Hellouin de Menibus , Takeaki Uno

We consider two optimization problems in planar graphs. In Maximum Weight Independent Set of Objects we are given a graph $G$ and a family $\mathcal{D}$ of objects, each being a connected subgraph of $G$ with a prescribed weight, and the…

Data Structures and Algorithms · Computer Science 2018-07-23 Michał Pilipczuk , Erik Jan van Leeuwen , Andreas Wiese

Estimating the probabilities of linkages in a network has gained increasing interest in recent years. One popular model for network analysis is the exchangeable graph model (ExGM) characterized by a two-dimensional function known as a…

Methodology · Statistics 2018-09-05 Yi Su , Raymond K. W. Wong , Thomas C. M. Lee

We study the family of intersection graphs of low density objects in low dimensional Euclidean space. This family is quite general, and includes planar graphs. We prove that such graphs have small separators. Next, we present efficient…

Computational Geometry · Computer Science 2016-06-01 Sariel Har-Peled , Kent Quanrud

For graphs $G$ and $H$, we say that $G$ is $H$-free if it does not contain $H$ as an induced subgraph. Already in the early 1980s Alekseev observed that if $H$ is connected, then the \textsc{Max Weight Independent Set} problem (MWIS)…

Data Structures and Algorithms · Computer Science 2022-02-09 Tara Abrishami , Maria Chudnovsky , Cemil Dibek , Paweł Rzążewski

We present the first polynomial self-stabilizing algorithm for finding a $\frac23$-approximation of a maximum matching in a general graph. The previous best known algorithm has been presented by Manne \emph{et al.} \cite{ManneMPT11} and has…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-21 Johanne Cohen , Khaled Maâmra , George Manoussakis , Laurence Pilard

This paper deals with the problem of finding, for a given graph and a given natural number k, a subgraph of k nodes with a maximum number of edges. This problem is known as the k-cluster problem and it is NP-hard on general graphs as well…

Data Structures and Algorithms · Computer Science 2011-11-09 George B. Mertzios

Gromov-Hausdorff distances measure shape difference between the objects representable as compact metric spaces, e.g. point clouds, manifolds, or graphs. Computing any Gromov-Hausdorff distance is equivalent to solving an NP-Hard…

Computational Geometry · Computer Science 2024-06-07 Vladyslav Oles , Nathan Lemons , Alexander Panchenko

This paper is motivated by the question whether there exists a logic capturing polynomial time computation over unordered structures. We consider several algorithmic problems near the border of the known, logically defined complexity…

Logic · Mathematics 2007-05-23 Andreas Blass , Yuri Gurevich , Saharon Shelah

This paper introduces the \emph{$d$-distance matching problem}, in which we are given a bipartite graph $G=(S,T;E)$ with $S=\{s_1,\dots,s_n\}$, a weight function on the edges and an integer $d\in\mathbb Z_+$. The goal is to find a maximum…

Combinatorics · Mathematics 2023-01-24 Péter Madarasi

We present the first polynomial-time approximation schemes, i.e., (1 + {\epsilon})-approximation algorithm for any constant {\epsilon} > 0, for the minimum three-edge connected spanning subgraph problem and the minimum three-vertex…

Data Structures and Algorithms · Computer Science 2017-01-31 Baigong Zheng

Arising from structural graph theory, treewidth has become a focus of study in fixed-parameter tractable algorithms in various communities including combinatorics, integer-linear programming, and numerical analysis. Many NP-hard problems…

Data Structures and Algorithms · Computer Science 2023-09-14 Sally Dong , Yin Tat Lee , Guanghao Ye

Suppose that we are given an arbitrary graph $G=(V, E)$ and know that each edge in $E$ is going to be realized independently with some probability $p$. The goal in the stochastic matching problem is to pick a sparse subgraph $Q$ of $G$ such…

Data Structures and Algorithms · Computer Science 2020-02-28 Soheil Behnezhad , Mahsa Derakhshan , MohammadTaghi Hajiaghayi

This paper addresses the problem of matching $N$ weighted graphs referring to an identical object or category. More specifically, matching the common node correspondences among graphs. This multi-graph matching problem involves two…

Computer Vision and Pattern Recognition · Computer Science 2016-06-14 Junchi Yan , Minsu Cho , Hongyuan Zha , Xiaokang Yang , Stephen Chu

As it follows from G\"odel's incompleteness theorems, any consistent formal system of axioms and rules of inference should imply a true unprovable statement. Actually, this fundamental principle can be efficiently applicable in…

Data Structures and Algorithms · Computer Science 2020-11-25 Roman Galay , Daniil Kalistratov

The Induced Graph Matching problem asks to find k disjoint induced subgraphs isomorphic to a given graph H in a given graph G such that there are no edges between vertices of different subgraphs. This problem generalizes the classical…

Discrete Mathematics · Computer Science 2014-02-11 Danny Hermelin , Matthias Mnich , Erik Jan van Leeuwen

In this paper, we study the computational complexity of finding the \emph{geodetic number} of graphs. A set of vertices $S$ of a graph $G$ is a \emph{geodetic set} if any vertex of $G$ lies in some shortest path between some pair of…

Discrete Mathematics · Computer Science 2020-12-08 Dibyayan Chakraborty , Florent Foucaud , Harmender Gahlawat , Subir Kumar Ghosh , Bodhayan Roy

Graph Neural Networks (GNNs) exploit signals from node features and the input graph topology to improve node classification task performance. However, these models tend to perform poorly on heterophilic graphs, where connected nodes have…

Machine Learning · Computer Science 2021-12-08 Vijay Lingam , Chanakya Ekbote , Manan Sharma , Rahul Ragesh , Arun Iyer , Sundararajan Sellamanickam

Combinatorial optimization algorithms for graph problems are usually designed afresh for each new problem with careful attention by an expert to the problem structure. In this work, we develop a new framework to solve any combinatorial…

We investigate novel random graph embeddings that can be computed in expected polynomial time and that are able to distinguish all non-isomorphic graphs in expectation. Previous graph embeddings have limited expressiveness and either cannot…

Machine Learning · Computer Science 2023-08-25 Pascal Welke , Maximilian Thiessen , Fabian Jogl , Thomas Gärtner
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