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Graph coarsening is a technique for solving large-scale graph problems by working on a smaller version of the original graph, and possibly interpolating the results back to the original graph. It has a long history in scientific computing…

Machine Learning · Computer Science 2023-06-16 Yifan Chen , Rentian Yao , Yun Yang , Jie Chen

The ability to compute similarity scores between graphs based on metrics such as Graph Edit Distance (GED) is important in many real-world applications. Computing exact GED values is typically an NP-hard problem and traditional algorithms…

Machine Learning · Computer Science 2022-08-18 Haoyan Xu , Runjian Chen , Yueyang Wang , Ziheng Duan , Jie Feng

An obstacle representation of a graph is a mapping of the vertices onto points in the plane and a set of connected regions of the plane (called obstacles) such that the straight-line segment connecting the points corresponding to two…

Graph, as an important data representation, is ubiquitous in many real world applications ranging from social network analysis to biology. How to correctly and effectively learn and extract information from graph is essential for a large…

Machine Learning · Computer Science 2020-10-27 Xiaodong Jiang , Ronghang Zhu , Pengsheng Ji , Sheng Li

This paper studies the problem of recovering the hidden vertex correspondence between two edge-correlated random graphs. We focus on the Gaussian model where the two graphs are complete graphs with correlated Gaussian weights and the…

Statistics Theory · Mathematics 2022-02-17 Yihong Wu , Jiaming Xu , Sophie H. Yu

Graph similarity computation is one of the core operations in many graph-based applications, such as graph similarity search, graph database analysis, graph clustering, etc. Since computing the exact distance/similarity between two graphs…

Machine Learning · Computer Science 2021-05-18 Yunsheng Bai , Hao Ding , Yizhou Sun , Wei Wang

We consider three variants of the problem of finding a maximum weight restricted $2$-matching in a subcubic graph $G$. (A $2$-matching is any subset of the edges such that each vertex is incident to at most two of its edges.) Depending on…

Data Structures and Algorithms · Computer Science 2021-01-01 Katarzyna Paluch , Mateusz Wasylkiewicz

We investigate the two problems of computing the union join graph as well as computing the subset graph for acyclic hypergraphs and their subclasses. In the union join graph $G$ of an acyclic hypergraph $H$, each vertex of $G$ represents a…

Data Structures and Algorithms · Computer Science 2021-04-15 Arne Leitert

Given a graph $G=(V,E)$, a set $\mathcal{F}$ of forbidden subgraphs, we study $\mathcal{F}$-Free Edge Deletion, where the goal is to remove minimum number of edges such that the resulting graph does not contain any $F\in \mathcal{F}$ as a…

Data Structures and Algorithms · Computer Science 2021-02-12 Ajinkya Gaikwad , Soumen Maity

Persistence diagrams (PD)s play a central role in topological data analysis. This analysis requires computing distances among such diagrams such as the $1$-Wasserstein distance. Accurate computation of these PD distances for large data sets…

Computational Geometry · Computer Science 2025-05-13 Tamal K. Dey , Simon Zhang

Complex systems frequently exhibit multi-way, rather than pairwise, interactions. These group interactions cannot be faithfully modeled as collections of pairwise interactions using graphs and instead require hypergraphs. However, methods…

Discrete Mathematics · Computer Science 2024-11-25 Jason Niu , Ilya D. Amburg , Sinan G. Aksoy , Ahmet Erdem Sarıyüce

We contribute an approach to the problem of locally computing sparse connected subgraphs of dense graphs. In this setting, given an edge in a connected graph $G = (V, E)$, an algorithm locally decides its membership in a sparse connected…

Data Structures and Algorithms · Computer Science 2020-07-13 Rogers Epstein

We investigate sublinear-time algorithms that take partially erased graphs represented by adjacency lists as input. Our algorithms make degree and neighbor queries to the input graph and work with a specified fraction of adversarial…

Data Structures and Algorithms · Computer Science 2020-12-01 Amit Levi , Ramesh Krishnan S. Pallavoor , Sofya Raskhodnikova , Nithin Varma

In this paper, we relate the problem of finding a maximum clique to the intersection number of the input graph (i.e. the minimum number of cliques needed to edge cover the graph). In particular, we consider the maximum clique problem for…

Discrete Mathematics · Computer Science 2012-04-19 S. Nikoletseas , C. Raptopoulos , P. G. Spirakis

A geometric graph is a graph whose vertices are points in general position in the plane and its edges are straight line segments joining these points. In this paper we give an $O(n^2 \log n)$ algorithm to compute the number of pairs of…

Computational Geometry · Computer Science 2020-09-04 Frank Duque , Ruy Fabila-Monroy , César Hernández-Vélez , Carlos Hidalgo-Toscano

Given an edge-weighted graph $G$ on $n$ nodes, the NP-hard Max-Cut problem asks for a node bipartition such that the sum of edge weights joining the different partitions is maximized. We propose a fixed-parameter tractable algorithm…

Data Structures and Algorithms · Computer Science 2020-07-23 Markus Chimani , Christine Dahn , Martina Juhnke-Kubitzke , Nils M. Kriege , Petra Mutzel , Alexander Nover

Subgraph matching is to find all subgraphs in a data graph that are isomorphic to an existing query graph. Subgraph matching is an NP-hard problem, yet has found its applications in many areas. Many learning-based methods have been proposed…

Discrete Mathematics · Computer Science 2022-11-09 Zixun Lan , Ye Ma , Limin Yu , LingLong Yuan , Fei Ma

Intersection graphs are well-studied in the area of graph algorithms. Some intersection graph classes are known to have algorithms enumerating all unlabeled graphs by reverse search. Since these algorithms output graphs one by one and the…

Data Structures and Algorithms · Computer Science 2022-12-15 Jun Kawahara , Toshiki Saitoh , Hirokazu Takeda , Ryo Yoshinaka , Yui Yoshioka

How efficiently can we find an unknown graph using distance or shortest path queries between its vertices? Let $G = (V,E)$ be an unweighted, connected graph of bounded degree. The edge set $E$ is initially unknown, and the graph can be…

Data Structures and Algorithms · Computer Science 2015-02-19 Sampath Kannan , Claire Mathieu , Hang Zhou

The emergence of geometric deep learning as a novel framework to deal with graph-based representations has faded away traditional approaches in favor of completely new methodologies. In this paper, we propose a new framework able to combine…

Computer Vision and Pattern Recognition · Computer Science 2020-08-19 Pau Riba , Andreas Fischer , Josep Lladós , Alicia Fornés