Results 281 to 290 of about 61,219 (309)
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Dominating Sets in Chordal Graphs
SIAM Journal on Computing, 1982A set of vertices D is a dominating set for a graph if every vertex is either in D or adjacent to a vertex which is in D. We show that the problem of finding a minimum dominating set in a chordal graph is NP-complete, even when restricted to undirected path graphs, but exhibit a linear time greedy algorithm for the problem further restricted to ...
Kellogg S. Booth, J. Howard Johnson
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Biclustering with dominant sets
Pattern Recognition, 2020Abstract Biclustering can be defined as the simultaneous clustering of rows and columns in a data matrix and it has been recently applied to many scientific scenarios such as bioinformatics, text analysis and computer vision to name a few. In this paper we propose a novel biclustering approach, that is based on the concept of dominant-set clustering ...
Denitto, M. +4 more
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On Dominating Sets and Independent Sets of Graphs
Combinatorics, Probability and Computing, 1999For a graph G on vertex set V = {1, …, n} let k = (k1, …, kn) be an integral vector such that 1 [les ] ki [les ] di for i ∈ V, where di is the degree of the vertex i in G. A k-dominating set is a set Dk ⊆ V such that every vertex i ∈ V[setmn ]Dk has at least ki neighbours in Dk.
Jochen Harant +2 more
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The Extended Dominating Sets in Graphs
Asia-Pacific Journal of Operational Research, 2023Let [Formula: see text] be a graph and let [Formula: see text] be an integer. A vertex subset [Formula: see text] is called a [Formula: see text]-extended dominating set if every vertex [Formula: see text] of [Formula: see text] satisfies one of the following conditions: the distance between [Formula: see text] and [Formula: see text] is at most one ...
Zhipeng Gao +3 more
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Dominant-set clustering: A review
European Journal of Operational Research, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Samuel Rota Bulò, Marcello Pelillo
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Dominant Sets and Pairwise Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007We develop a new graph-theoretic approach for pairwise data clustering which is motivated by the analogies between the intuitive concept of a cluster and that of a dominant set of vertices, a notion introduced here which generalizes that of a maximal complete subgraph to edge-weighted graphs.
PAVAN M, PELILLO, Marcello
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2018
Biclustering, which can be defined as the simultaneous clustering of rows and columns in a data matrix, has received increasing attention in recent years, being applied in many scientific scenarios (e.g. bioinformatics, text analysis, computer vision).
M. Denitto +3 more
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Biclustering, which can be defined as the simultaneous clustering of rows and columns in a data matrix, has received increasing attention in recent years, being applied in many scientific scenarios (e.g. bioinformatics, text analysis, computer vision).
M. Denitto +3 more
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Liar’s dominating sets in graphs
Discrete Applied Mathematics, 2016zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Abdollah Alimadadi +2 more
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SIAM Journal on Discrete Mathematics, 1993
Let \(G=(V,E)\) be a finite graph. The cardinality of \(V\) (the set of vertices) is \(n\) and the cardinality of \(E\) (the set of edges) is \(m\). Define the following relation of \(E\): \(e\succeq e'\) iff either \(e=e'\) or \(e\) and \(e'\) are adjacent. A subset \(D\subseteq E\) is called an edge dominating set if for each \(e'\in E\) there is \(e\
Joseph Douglas Horton, Kyriakos Kilakos
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Let \(G=(V,E)\) be a finite graph. The cardinality of \(V\) (the set of vertices) is \(n\) and the cardinality of \(E\) (the set of edges) is \(m\). Define the following relation of \(E\): \(e\succeq e'\) iff either \(e=e'\) or \(e\) and \(e'\) are adjacent. A subset \(D\subseteq E\) is called an edge dominating set if for each \(e'\in E\) there is \(e\
Joseph Douglas Horton, Kyriakos Kilakos
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Constrained dominant sets for retrieval
2016 23rd International Conference on Pattern Recognition (ICPR), 2016Learning new global relations based on an initial affinity of the database objects has shown significant improvements in similarity retrievals. Locally constrained diffusion process is one of the recent effective tools in learning the intrinsic manifold structure of a given data.
MEQUANINT, EYASU ZEMENE +2 more
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