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For a clustered graph, i.e, a graph whose vertex set is recursively partitioned into clusters, the C-Planarity Testing problem asks whether it is possible to find a planar embedding of the graph and a representation of each cluster as a…

Data Structures and Algorithms · Computer Science 2021-08-18 Giordano Da Lozzo , David Eppstein , Michael T. Goodrich , Siddharth Gupta

Graph embedding aims to transfer a graph into vectors to facilitate subsequent graph analytics tasks like link prediction and graph clustering. Most approaches on graph embedding focus on preserving the graph structure or minimizing the…

Machine Learning · Computer Science 2020-03-04 Shirui Pan , Ruiqi Hu , Sai-fu Fung , Guodong Long , Jing Jiang , Chengqi Zhang

In the point set embeddability problem, we are given a plane graph $G$ with $n$ vertices and a point set $S$ with $n$ points. Now the goal is to answer the question whether there exists a straight-line drawing of $G$ such that each vertex…

Computational Geometry · Computer Science 2020-05-13 Tanaeem M. Moosa , M. Sohel Rahman

In recent years, graph representation learning has gained significant popularity, which aims to generate node embeddings that capture features of graphs. One of the methods to achieve this is employing a technique called random walks that…

Machine Learning · Computer Science 2022-10-13 Deniz Gurevin , Mohsin Shan , Tong Geng , Weiwen Jiang , Caiwen Ding , Omer Khan

We give a distributed algorithm in the {\sf CONGEST} model for property testing of planarity with one-sided error in general (unbounded-degree) graphs. Following Censor-Hillel et al. (DISC 2016), who recently initiated the study of property…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-15 Reut Levi , Moti Medina , Dana Ron

Graph embedding (GE) methods embed nodes (and/or edges) in graph into a low-dimensional semantic space, and have shown its effectiveness in modeling multi-relational data. However, existing GE models are not practical in real-world…

Machine Learning · Computer Science 2020-11-25 Xiaoyu Kou , Yankai Lin , Shaobo Liu , Peng Li , Jie Zhou , Yan Zhang

Given a `genus' function $g=g(n)$, we let $\mathcal{E}^g$ be the class of all graphs $G$ such that if $G$ has order $n$ (that is, has $n$ vertices) then it is embeddable in a surface of Euler genus at most $g(n)$. Let the random graph $R_n$…

Combinatorics · Mathematics 2021-08-18 Colin McDiarmid , Sophia Saller

A key concept for many graph layout algorithms is planarity, a graph property that allows to draw vertices and edges crossing-free in the plane. Important is the generalization to $k$-planar graphs, which can be drawn in the plane with at…

Discrete Mathematics · Computer Science 2026-05-18 Aaron Büngener , Jakob Franz , Michael Kaufmann , Maximilian Pfister

In a book embedding, the vertices of a graph are placed on the spine of a book and the edges are assigned to pages, so that edges on the same page do not cross. In this paper, we prove that every $1$-planar graph (that is, a graph that can…

Data Structures and Algorithms · Computer Science 2015-03-31 Michael A. Bekos , Till Bruckdorfer , Michael Kaufmann , Chrysanthi N. Raftopoulou

In an upward-planar L-drawing of a directed acyclic graph (DAG) each edge $e$ is represented as a polyline composed of a vertical segment with its lowest endpoint at the tail of $e$ and of a horizontal segment ending at the head of $e$.…

Data Structures and Algorithms · Computer Science 2022-08-04 Patrizio Angelini , Steven Chaplick , Sabine Cornelsen , Giordano Da Lozzo

A graph is NIC-planar if it admits a drawing in the plane with at most one crossing per edge and such that two pairs of crossing edges share at most one common end vertex. NIC-planarity generalizes IC-planarity, which allows a vertex to be…

Discrete Mathematics · Computer Science 2017-11-06 Christian Bachmaier , Franz J. Brandenburg , Kathrin Hanauer , Daniel Neuwirth , Josef Reislhuber

Mapping complex input data into suitable lower dimensional manifolds is a common procedure in machine learning. This step is beneficial mainly for two reasons: (1) it reduces the data dimensionality and (2) it provides a new data…

Machine Learning · Computer Science 2018-11-28 Daniele Zambon , Lorenzo Livi , Cesare Alippi

Let $G$ be a finite undirected graph with edge set $E$. An edge set $E' \subseteq E$ is an {\em induced matching} in $G$ if the pairwise distance of the edges of $E'$ in $G$ is at least two; $E'$ is {\em dominating} in $G$ if every edge $e…

Discrete Mathematics · Computer Science 2011-06-15 Andreas Brandstadt , Raffaele Mosca

In this paper, we introduce a method called graph fusion embedding, designed for multi-graph embedding with shared vertex sets. Under the framework of supervised learning, our method exhibits a remarkable and highly desirable synergistic…

Social and Information Networks · Computer Science 2024-06-27 Cencheng Shen , Carey E. Priebe , Jonathan Larson , Ha Trinh

While orthogonal drawings have a long history, smooth orthogonal drawings have been introduced only recently. So far, only planar drawings or drawings with an arbitrary number of crossings per edge have been studied. Recently, a lot of…

Recent years have seen a rise in the development of representational learning methods for graph data. Most of these methods, however, focus on node-level representation learning at various scales (e.g., microscopic, mesoscopic, and…

Machine Learning · Computer Science 2021-11-18 Lili Wang , Chenghan Huang , Weicheng Ma , Xinyuan Cao , Soroush Vosoughi

It was conjectured by Gupta et al. [Combinatorica04] that every planar graph can be embedded into $\ell_1$ with constant distortion. However, given an $n$-vertex weighted planar graph, the best upper bound on the distortion is only…

Data Structures and Algorithms · Computer Science 2024-07-30 Arnold Filtser

This paper presents the first parallel batch-dynamic algorithms for computing spanners and sparsifiers. Our algorithms process any batch of edge insertions and deletions in an $n$-node undirected graph, in $\text{poly}(\log n)$ depth and…

Data Structures and Algorithms · Computer Science 2025-07-10 Mohsen Ghaffari , Jaehyun Koo

We present a simple randomized algorithm that can efficiently maintain a $(\Delta+1)$ coloring as the graph undergoes edge insertion and deletion updates, where $\Delta$ denotes an upper bound on the maximum degree. A key advantage is the…

Data Structures and Algorithms · Computer Science 2025-12-11 Mohsen Ghaffari , Jaehyun Koo

Maintaining a $k$-core decomposition quickly in a dynamic graph has important applications in network analysis. The main challenge for designing efficient exact algorithms is that a single update to the graph can cause significant global…

Data Structures and Algorithms · Computer Science 2023-09-28 Quanquan C. Liu , Jessica Shi , Shangdi Yu , Laxman Dhulipala , Julian Shun
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