Speeding up the convergence of the alternating least squares algorithm using vector őĶ acceleration and restarting for nonlinear principal component analysis. | D2R Server publishing the DBLP Bibliography Database, hosted at L3S Research Center

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dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Masahiro_Kuroda>
dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Masaya_Iizuka>
dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Yuichi_Mori>
foaf:homepage	<http://dx.doi.org/doi.org%2F10.1007%2Fs00180-022-01225-4>
foaf:homepage	<https://doi.org/10.1007/s00180-022-01225-4>
dc:identifier	DBLP journals/cstat/KurodaMI23 (xsd:string)
dc:identifier	DOI doi.org%2F10.1007%2Fs00180-022-01225-4 (xsd:string)
dcterms:issued	2023 (xsd:gYear)
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rdfs:label	Speeding up the convergence of the alternating least squares algorithm using vector őĶ acceleration and restarting for nonlinear principal component analysis. (xsd:string)
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foaf:maker	<https://dblp.l3s.de/d2r/resource/authors/Yuichi_Mori>
swrc:month	March (xsd:string)
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swrc:pages	243-262 (xsd:string)
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rdfs:seeAlso	<https://doi.org/10.1007/s00180-022-01225-4>
dc:title	Speeding up the convergence of the alternating least squares algorithm using vector őĶ acceleration and restarting for nonlinear principal component analysis. (xsd:string)
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