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Can I read Chapman & Hall/crc Machine Learning & Pattern Recognition Series Multilinear Subspace Learning Dimensionality Reduction of Multidimensional Data,haiping Lu on EtoBox?
Chapman & Hall/crc Machine Learning & Pattern Recognition Series Multilinear Subspace Learning Dimensionality Reduction of Multidimensional Data,haiping Lu by Lu, Haiping ;Plataniotis, Konstantinos N. ;Venetsanopoulos, Anastasios is a nonfiction available to read on EtoBox.
What is Chapman & Hall/crc Machine Learning & Pattern Recognition Series Multilinear Subspace Learning Dimensionality Reduction of Multidimensional Data,haiping Lu about?
"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 Multidimensional Data gives a comprehensive introduction to both theoretical and practical aspects of MSL for the dimensionality reduction of multidimensional data based on tensors. It covers the fundamentals, algorithms, and applications of MSL. Emphasizing essential concepts and system-level perspectives, the authors provide a foundation for solving many of today's most interesting and challenging problems in big multidimensional data processing. They trace the history of MSL, detail recent advances, and explore future developments and emerging applications. The book follows a unifying MSL framework formulation
Who reads Chapman & Hall/crc Machine Learning & Pattern Recognition Series Multilinear Subspace Learning Dimensionality Reduction of Multidimensional Data,haiping Lu?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Lu, Haiping ;Plataniotis, Konstantinos N. ;Venetsanopoulos, Anastasios
- Publisher
- Chapman and Hall/CRC
- Published
- 2013
- Language
- EN
- ISBN
- 9781466538092
- Category
- nonfiction
- Subjects
- Engineering, Mathematics, Science
Other editions & translations
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