Vai al contenuto principale della pagina

Multilinear subspace learning : dimensionality reduction of multidimensional data / / Haiping Lu, K. N. Plataniotis, A. N. Venetsanopoulos



(Visualizza in formato marc)    (Visualizza in BIBFRAME)

Autore: Lu Haiping Visualizza persona
Titolo: Multilinear subspace learning : dimensionality reduction of multidimensional data / / Haiping Lu, K. N. Plataniotis, A. N. Venetsanopoulos Visualizza cluster
Pubblicazione: Boca Raton, Florida : , : CRC Press, , 2014
©2014
Descrizione fisica: 1 online resource (275 p.)
Disciplina: 005.7
Soggetto topico: Data compression (Computer science)
Big data
Multilinear algebra
Classificazione: COM021030COM037000TEC007000
Altri autori: PlataniotisK. N  
VenetsanopoulosA. N  
Note generali: Description based upon print version of record.
Nota di bibliografia: Includes bibliographical references.
Nota di contenuto: Front Cover; Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data; Copyright; Dedication; Table of Contents; List of Figures; List of Tables; List of Algorithms; Acronyms and Symbols; Preface; 1. Introduction; Part I: Fundamentals and Foundations; 2. Linear Subspace Learning for Dimensionality Reduction; 3. Fundamentals of Multilinear Subspace Learning; 4. Overview of Multilinear Subspace Learning; 5. Algorithmic and Computational Aspects; Part II: Algorithms and Applications; 6. Multilinear Principal Component Analysis; 7. Multilinear Discriminant Analysis
8. Multilinear ICA, CCA, and PLS9. Applications of Multilinear Subspace Learning; Appendix A: Mathematical Background; Appendix B: Data and Preprocessing; Appendix C: Software; Bibliography; Back Cover
Sommario/riassunto: Due to advances in sensor, storage, and networking technologies, data is being generated on a daily basis at an ever-increasing pace in a wide range of applications, including cloud computing, mobile Internet, and medical imaging. This large multidimensional data requires more efficient dimensionality reduction schemes than the traditional techniques. Addressing this need, multilinear subspace learning (MSL) reduces the dimensionality of big data directly from its natural multidimensional representation, a tensor.Multilinear Subspace Learning: Dimensionality Reduction of Mult
Titolo autorizzato: Multilinear subspace learning  Visualizza cluster
ISBN: 0-429-10809-5
1-4398-5729-6
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910821414003321
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui