Zobrazeno 1 - 10
of 118
pro vyhledávání: '"Wierzchoń, Sławomir T."'
Our previous experiments demonstrated that subsets collections of (short) documents (with several hundred entries) share a common normalized in some way eigenvalue spectrum of combinatorial Laplacian. Based on this insight, we propose a method of inc
Externí odkaz:
http://arxiv.org/abs/2308.10999
Spectral clustering methods are known for their ability to represent clusters of diverse shapes, densities etc. However, results of such algorithms, when applied e.g. to text documents, are hard to explain to the user, especially due to embedding in
Externí odkaz:
http://arxiv.org/abs/2308.00504
Valuation-Based~System can represent knowledge in different domains including probability theory, Dempster-Shafer theory and possibility theory. More recent studies show that the framework of VBS is also appropriate for representing and solving Bayes
Externí odkaz:
http://arxiv.org/abs/1909.12032
Mathematical Theory of Evidence (MTE), a foundation for reasoning under partial ignorance, is blamed to leave frequencies outside (or aside of) its framework. The seriousness of this accusation is obvious: no experiment may be run to compare the perf
Externí odkaz:
http://arxiv.org/abs/1812.02942
Publikováno v:
This is the preliminary version of the paper published in Demonstratio Mathematica. Vol XXXI No 3,1998, pp. 669-688
The paper presents a novel view of the Dempster-Shafer belief function as a measure of diversity in relational data bases. It is demonstrated that under the interpretation The Dempster rule of evidence combination corresponds to the join operator of
Externí odkaz:
http://arxiv.org/abs/1704.02468
Akademický článek
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Autor:
Kłopotek, Mieczysław A.1 (AUTHOR) klopotek@ipipan.waw.pl, Wierzchoń, Sławomir T.1 (AUTHOR), Kłopotek, Robert A.1 (AUTHOR)
Publikováno v:
Fundamenta Informaticae. 2022, Vol. 189 Issue 1, p49-68. 20p.
Publikováno v:
International Journal of Applied Mathematics and Computer Science, Vol 28, Iss 4, Pp 771-786 (2018)
The paper presents a novel spectral algorithm EVSA (eigenvector structure analysis), which uses eigenvalues and eigenvectors of the adjacency matrix in order to discover clusters. Based on matrix perturbation theory and properties of graph spectra we
Externí odkaz:
https://doaj.org/article/b41763064aa74293b6c45056446fad5f
Akademický článek
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