Isbn: 9783319039428 - open problems in spectral dimensionality reduction (9 risultati)

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  • Lingua: Inglese

    Editore: Springer, 2014

    3319039423 / 9783319039428

    Serie: Libro 113 di 322 - SpringerBriefs in Computer Science

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    Condizione: New. In English.

  • Lingua: Inglese

    Editore: Springer 2014-01, 2014

    3319039423 / 9783319039428

    Serie: Libro 113 di 322 - SpringerBriefs in Computer Science

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    Da: Chiron Media, Wallingford, Regno UnitoChiron Media

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  • Lingua: Inglese

    Editore: Springer, 2014

    3319039423 / 9783319039428

    Serie: Libro 113 di 322 - SpringerBriefs in Computer Science

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    Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books

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    Paperback. Condizione: Brand New. 2014 edition. 92 pages. 8.75x6.25x0.25 inches. In Stock.

  • Lingua: Inglese

    Editore: Springer, 2014

    3319039423 / 9783319039428

    Serie: Libro 113 di 322 - SpringerBriefs in Computer Science

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The last few years have seen a great increase in the amount of data available to scientists, yet many of the techniques used to analyse this data cannot cope with such large datasets. Therefore, strategies need to be employed as a pre-processing step to reduce the number of objects or measurements whilst retaining important information. Spectral dimensionality reduction is one such tool for the data processing pipeline. Numerous algorithms and improvements have been proposed for the purpose of performing spectral dimensionality reduction, yet there is still no gold standard technique. This book provides a survey and reference aimed at advanced undergraduate and postgraduate students as well as researchers, scientists, and engineers in a wide range of disciplines. Dimensionality reduction has proven useful in a wide range of problem domains and so this book will be applicable to anyone with a solid grounding in statistics and computer science seeking to apply spectral dimensionality to their work.

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    Lingua: Inglese

    Editore: Springer, 2014

    3319039423 / 9783319039428

    Serie: Libro 113 di 322 - SpringerBriefs in Computer Science

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    Taschenbuch. Condizione: Neu. Open Problems in Spectral Dimensionality Reduction | Harry Strange (u. a.) | Taschenbuch | SpringerBriefs in Computer Science | ix | Englisch | 2014 | Springer | EAN 9783319039428 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Lingua: Inglese

    Editore: Springer, 2014

    3319039423 / 9783319039428

    Serie: Libro 113 di 322 - SpringerBriefs in Computer Science

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    Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand

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    Condizione: new. Questo è un articolo print on demand.

  • Lingua: Inglese

    Editore: Springer International Publishing Jan 2014, 2014

    3319039423 / 9783319039428

    Serie: Libro 113 di 322 - SpringerBriefs in Computer Science

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The last few years have seen a great increase in the amount of data available to scientists, yet many of the techniques used to analyse this data cannot cope with such large datasets. Therefore, strategies need to be employed as a pre-processing step to reduce the number of objects or measurements whilst retaining important information. Spectral dimensionality reduction is one such tool for the data processing pipeline. Numerous algorithms and improvements have been proposed for the purpose of performing spectral dimensionality reduction, yet there is still no gold standard technique. This book provides a survey and reference aimed at advanced undergraduate and postgraduate students as well as researchers, scientists, and engineers in a wide range of disciplines. Dimensionality reduction has proven useful in a wide range of problem domains and so this book will be applicable to anyone with a solid grounding in statistics and computer science seeking to apply spectral dimensionality to their work. 104 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer International Publishing, 2014

    3319039423 / 9783319039428

    Serie: Libro 113 di 322 - SpringerBriefs in Computer Science

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    Da: moluna, Greven, Germaniamoluna

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a clear and concise overview of spectral dimensionality reductionOffers uniquely practical knowledge without requiring a background in the areaSuggests interesting starting points for future research in this areaThe last few years.

  • Lingua: Inglese

    Editore: Springer, Palgrave Macmillan Jan 2014, 2014

    3319039423 / 9783319039428

    Serie: Libro 113 di 322 - SpringerBriefs in Computer Science

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    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The last few years have seen a great increase in the amount of data available to scientists, yet many of the techniques used to analyse this data cannot cope with such large datasets. Therefore, strategies need to be employed as a pre-processing step to reduce the number of objects or measurements whilst retaining important information. Spectral dimensionality reduction is one such tool for the data processing pipeline. Numerous algorithms and improvements have been proposed for the purpose of performing spectral dimensionality reduction, yet there is still no gold standard technique. This book provides a survey and reference aimed at advanced undergraduate and postgraduate students as well as researchers, scientists, and engineers in a wide range of disciplines. Dimensionality reduction has proven useful in a wide range of problem domains and so this book will be applicable to anyone with a solid grounding in statistics and computer science seeking to apply spectral dimensionality to their work.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 104 pp. Englisch.