Yutaka Koshiba

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In this paper, first we discuss acceleration of classification by reducing support vectors. Then, we discuss multiclass least squares SVMs (LS-SVMs) that resolve unclassifiable regions for multiclass problems: fuzzy one-against-all LS-SVMs, fuzzy pairwise LS-SVMs, and all-at-once LS-SVMs. Next, we compare the three types of LS-SVMs from the standpoint of(More)
Service discovery and composition are challenging issue of service computing to provide value-added service. Existing approaches by keyword or ontology matching have limitations for locating realistic services discovery and composition considering non-functionality or sociality. On main reason in that approaches are based on isolated services. The isolation(More)
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