A fast algorithm for updating and downsizing the dominant kernel principal components (Articolo in rivista)

Type
Label
  • A fast algorithm for updating and downsizing the dominant kernel principal components (Articolo in rivista) (literal)
Anno
  • 2010-01-01T00:00:00+01:00 (literal)
Alternative label
  • Mastronardi N., Tyrtyshnikov E., Van Dooren P. (2010)
    A fast algorithm for updating and downsizing the dominant kernel principal components
    in SIAM journal on matrix analysis and applications (Print)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Mastronardi N., Tyrtyshnikov E., Van Dooren P. (literal)
Pagina inizio
  • 2376 (literal)
Pagina fine
  • 2399 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 31 (literal)
Rivista
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Istituto per le Applicazioni del Calcolo \"M. Picone\", CNR, Sede di Bari Institute of Numerical Mathematics, Russian Academy of Sciences, Moscow Department of Mathematical Engineering, Catholic University of Louvain, Louvain-la-Neuve, Belgium. (literal)
Titolo
  • A fast algorithm for updating and downsizing the dominant kernel principal components (literal)
Abstract
  • Many important kernel methods in the machine learning area, such as kernel principal component analysis, feature approximation, denoising, compression and prediction require the computation of the dominant set of eigenvectors of the symmetric kernel Gram matrix. Recently, an efficient incremental approach was presented for the fast calculation of the dominant kernel eigenbasis. In this manuscript we propose faster algorithms for incrementally updating and downsizing the dominant kernel eigenbasis. These methods are well-suited for large scale problems since they are both efficient in terms of complexity and data management. (literal)
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