Zobrazeno 1 - 10
of 242
pro vyhledávání: '"distance computation"'
Publikováno v:
Cybernetics and Information Technologies, Vol 22, Iss 2, Pp 36-49 (2022)
Learning Vector Quantization (LVQ) is one of the most widely used classification approaches. LVQ faces a problem as when the size of data grows large it becomes slower. In this paper, a modified version of LVQ, which is called PDLVQ is proposed to ac
Externí odkaz:
https://doaj.org/article/d0037f682795414fb6790d5845ff5238
Publikováno v:
IEEE Access, Vol 8, Pp 16456-16461 (2020)
Secure Manhattan distance computation allows two parties to privately compute the Manhattan distance of their points, which is important and has broad applications. In this paper, we present a protocol for secure Manhattan distance computation based
Externí odkaz:
https://doaj.org/article/cef1b83b1b3b4a8a8ffe6682b2b62bf7
Publikováno v:
IEEE Access, Vol 8, Pp 191673-191682 (2020)
Given a large graph, such as a social network or a knowledge graph, a fundamental query is how to find the distance from a source vertex to another vertex in the graph. As real graphs become very large and many distributed graph systems, such as Preg
Externí odkaz:
https://doaj.org/article/c504a62aea054b898e34b0347908f03d
Autor:
César González, Simone Balocco, Jaume Bosch, Juan Miguel de Haro, Maurizio Paolini, Antonio Filgueras, Carlos Álvarez, Ramon Pons
Publikováno v:
International Journal of Molecular Sciences, Vol 23, Iss 19, p 11408 (2022)
X-ray crystallography is a powerful method that has significantly contributed to our understanding of the biological function of proteins and other molecules. This method relies on the production of crystals that, however, are usually a bottleneck in
Externí odkaz:
https://doaj.org/article/2477a2d9993f439d85b3a0344fbcc975
Akademický článek
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Akademický článek
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Publikováno v:
Tongxin xuebao, Vol 38, Pp 127-134 (2017)
In the high-dimensional vector retrieval,distance computation is a very time-consuming operation,the current research trend is to reduce the distance computation using divide and conquer algorithm.iDistance algorithm divides the vector space into sub
Externí odkaz:
https://doaj.org/article/77143003bc9d40799d065b10179b6cde
Publikováno v:
UHD Journal of Science and Technology, Vol 1, Iss 2, Pp 13-24 (2017)
In this paper, we introduce an improved parallel algorithm for computing the number of exact matches nid (S,T) in the local alignment of two biological sequences S and T. This number is used in the first stage of progressive alignment to compute the
Externí odkaz:
https://doaj.org/article/90dec4df9acb4f1e823ab729ca572cb5
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 1, Iss 1, Pp 159-174 (2016)
In this article, we propose an ontology learning algorithm for ontology similarity measure and ontology mapping in view of distance function learning techniques. Using the distance computation formulation, all the pairs of ontology vertices are mappe
Externí odkaz:
https://doaj.org/article/06561d262cf9412b982a979d4f9dda7b
Akademický článek
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