Regularization, Optimization, Kernels, and Support Vector Machines -
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This book is a collection of invited contributions from leading researchers in machine learning. Comprised of 21 chapters, this comprehensive reference covers the latest research and advances in regularization, sparsity, and compressed sensing; describes recent progress in convex and large-scale optimization, kernel methods, and support vector machines; and discusses output kernel learning, domain adaptatio ... Full description
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Description
This book is a collection of invited contributions from leading researchers in machine learning. Comprised of 21 chapters, this comprehensive reference covers the latest research and advances in regularization, sparsity, and compressed sensing; describes recent progress in convex and large-scale optimization, kernel methods, and support vector machines; and discusses output kernel learning, domain adaptation, multi-layer support vector machines, and more.
More Information
| Publisher | CRC Press |
|---|---|
| Release year | 2014 |
| Cover type | Hardcover |
| EAN | 9781482241396 |