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Regularization, Optimization, Kernels, and Support Vector Machines (Hardcover) Loot Price: R3,216
Discovery Miles 32 160
Regularization, Optimization, Kernels, and Support Vector Machines (Hardcover): Johan A.K. Suykens, Marco Signoretto, Andreas...

Regularization, Optimization, Kernels, and Support Vector Machines (Hardcover)

Johan A.K. Suykens, Marco Signoretto, Andreas Argyriou

Series: Chapman & Hall/CRC Machine Learning & Pattern Recognition

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Loot Price R3,216 Discovery Miles 32 160 | Repayment Terms: R301 pm x 12*

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Regularization, Optimization, Kernels, and Support Vector Machines offers a snapshot of the current state of the art of large-scale machine learning, providing a single multidisciplinary source for the latest research and advances in regularization, sparsity, compressed sensing, convex and large-scale optimization, kernel methods, and support vector machines. Consisting of 21 chapters authored by leading researchers in machine learning, this comprehensive reference: Covers the relationship between support vector machines (SVMs) and the Lasso Discusses multi-layer SVMs Explores nonparametric feature selection, basis pursuit methods, and robust compressive sensing Describes graph-based regularization methods for single- and multi-task learning Considers regularized methods for dictionary learning and portfolio selection Addresses non-negative matrix factorization Examines low-rank matrix and tensor-based models Presents advanced kernel methods for batch and online machine learning, system identification, domain adaptation, and image processing Tackles large-scale algorithms including conditional gradient methods, (non-convex) proximal techniques, and stochastic gradient descent Regularization, Optimization, Kernels, and Support Vector Machines is ideal for researchers in machine learning, pattern recognition, data mining, signal processing, statistical learning, and related areas.

General

Imprint: Apple Academic Press Inc.
Country of origin: Canada
Series: Chapman & Hall/CRC Machine Learning & Pattern Recognition
Release date: October 2014
First published: 2015
Editors: Johan A.K. Suykens • Marco Signoretto • Andreas Argyriou
Dimensions: 234 x 156 x 32mm (L x W x T)
Format: Hardcover
Pages: 525
ISBN-13: 978-1-4822-4139-6
Categories: Books > Professional & Technical > Electronics & communications engineering > Communications engineering / telecommunications > General
Books > Computing & IT > Applications of computing > Databases > General
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > General
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LSN: 1-4822-4139-0
Barcode: 9781482241396

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