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Simultaneous Embedding of Embedded Planar Graphs
International Journal of Computational Geometry & Applications, 2011A simultaneous embedding with fixed edges (SEFE) of a set of k planar graphs G1,…,Gk on the same set of vertices is a set of k planar drawings of G1,…,Gk, respectively, such that each vertex is placed on the same point in all the drawings and each edge is represented by the same Jordan curve in the drawings of all the graphs it belongs to.
ANGELINI, PATRIZIO +2 more
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Graphs and Combinatorics, 2001
Let \(S\) be a quasiordered set (quoset) or topological space and \(\text{Sub} S\) be the set of all nonempty subquosets or subspaces quasiordered by embeddability, respectively. For a cardinal number \(n\), \(p_n\) and \(q_n\) denote the smallest size of spaces \(S\) such that each poset respectively quoset with \(n\) points is embeddable in \(\text ...
Erné, Marcel, Reinhold, Jürgen
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Let \(S\) be a quasiordered set (quoset) or topological space and \(\text{Sub} S\) be the set of all nonempty subquosets or subspaces quasiordered by embeddability, respectively. For a cardinal number \(n\), \(p_n\) and \(q_n\) denote the smallest size of spaces \(S\) such that each poset respectively quoset with \(n\) points is embeddable in \(\text ...
Erné, Marcel, Reinhold, Jürgen
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Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017
Network embedding is increasingly employed to assist network analysis as it is effective to learn latent features that encode linkage information. Various network embedding methods have been proposed, but they are only designed for a single network scenario.
Linchuan Xu +3 more
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Network embedding is increasingly employed to assist network analysis as it is effective to learn latent features that encode linkage information. Various network embedding methods have been proposed, but they are only designed for a single network scenario.
Linchuan Xu +3 more
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Journal of the American Statistical Association, 2020
Numerical embedding has become one standard technique for processing and analyzing unstructured data that cannot be expressed in a predefined fashion. It stores the main characteristics of data by mapping it onto a numerical vector. An embedding is often unsupervised and constructed by transfer learning from large-scale unannotated data.
Ben, Dai, Xiaotong, Shen, Junhui, Wang
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Numerical embedding has become one standard technique for processing and analyzing unstructured data that cannot be expressed in a predefined fashion. It stores the main characteristics of data by mapping it onto a numerical vector. An embedding is often unsupervised and constructed by transfer learning from large-scale unannotated data.
Ben, Dai, Xiaotong, Shen, Junhui, Wang
openaire +2 more sources