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The fixed set search applied to the power dominating set problem

Expert Syst. J. Knowl. Eng., 2020
In this article, we focus on solving the power dominating set problem and its connected version. These problems are frequently used for finding optimal placements of phasor measurement units in power systems. We present an improved integer linear program
R. Jovanovic, S. Voß
semanticscholar   +1 more source

Biclustering with dominant sets

Pattern Recognition, 2020
Abstract 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
openaire   +2 more sources

Distributed Dominating Set and Connected Dominating Set Construction Under the Dynamic SINR Model

IEEE International Parallel and Distributed Processing Symposium, 2019
This paper investigates distributed Dominating Set (DS) and Connected Dominating Set (CDS) construction in dynamic wireless networks under the SINR interference model. Specifically, we present a new model for dynamic networks that admits both churns (due
Dongxiao Yu   +7 more
semanticscholar   +1 more source

Dominant Sets and Pairwise Clustering

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007
We 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
openaire   +6 more sources

A Clustering Scheme for Wireless Sensor Networks Based on Genetic Algorithm and Dominating Set

, 2018
The basic K-center problem is a fundamental facility location problem. Given n vertices with some distances, one wants to build k facilities in different vertices, so as to minimize the maximum distance from a vertex to its corresponding facility.
Jeng‐Shyang Pan   +4 more
semanticscholar   +1 more source

Derandomizing Distributed Algorithms with Small Messages: Spanners and Dominating Set

International Symposium on Distributed Computing, 2018
This paper presents improved deterministic distributed algorithms, with O(logn)-bit messages, for some basic graph problems. The common ingredient in our results is a deterministic distributed algorithm for computing a certain hitting set, which can ...
M. Ghaffari, F. Kuhn
semanticscholar   +1 more source

Dominant Set Biclustering

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
openaire   +3 more sources

Dominating Sets in Web Graphs

2004
In this paper we study the size of generalised dominating sets in two graph processes which are widely used to model aspects of the world-wide web. On the one hand, we show that graphs generated this way have fairly large dominating sets (i.e. linear in the size of the graph).
Cooper, C, Klasing, R, Zito, M
openaire   +3 more sources

Dominating sets of centipedes

Journal of Discrete Mathematical Sciences and Cryptography, 2009
Abstract Let G = (V, E) be a simple graph. A set S ⊆ V is a dominating set of G, if every vertex in V − S is adjacent to at least one vertex in S. Let be the family of all dominating sets of a graph G with cardinality i, and G* be the graph obtained by appending a single pendant edge to each vertex of graph G.
Yee-Hock Peng, Saeid Alikhani
openaire   +2 more sources

Constrained dominant sets for retrieval

2016 23rd International Conference on Pattern Recognition (ICPR), 2016
Learning 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
openaire   +2 more sources

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