1 option
Multilinear subspace learning : dimensionality reduction of multidimensional data / Haiping Lu, K. N. Plataniotis, A. N. Venetsanopoulos.
- Format:
- Book
- Author/Creator:
- Lu, Haiping.
- Series:
- Chapman & Hall/CRC machine learning & pattern recognition series
- Chapman & Hall/CRC machine learning & pattern recognition series Multilinear subspace learning
- Language:
- English
- Subjects (All):
- Data compression (Computer science).
- Big data.
- Multilinear algebra.
- Physical Description:
- 1 online resource (275 p.)
- Edition:
- 1st ed.
- Place of Publication:
- Boca Raton, Florida : CRC Press, 2014.
- Language Note:
- English
- Summary:
- 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
- Contents:
- 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
- Notes:
- Description based upon print version of record.
- Includes bibliographical references.
- Description based on print version record.
- ISBN:
- 9781040197691
- 1040197698
- 9780429108099
- 0429108095
- 9781439857298
- 1439857296
- OCLC:
- 880788144
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.