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Regularization optimization kernels and support vector machines / edited by Johan A K Suykens, Marco Signoretto and Andreas Argyriou

Contributor(s): Material type: TextTextLanguage: English Publication details: Boca Raton : CRC Press. 2015,Description: xvii, 507p. : illISBN:
  • 9781482241396
Subject(s): Other classification:
  • D65,8(B):9 Q5 TOR
Summary: 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.
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Textbook Textbook Central Science Library Central Science Library D65,8(B):9 Q5 TOR (Browse shelf(Opens below)) Available SL1598105

Index 503-507p.

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.

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