Statistical Learning with Sparsity: The Lasso and Generalizations (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)
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:
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.
Country | USA |
Brand | CRC Press |
Manufacturer | Chapman and Hall/CRC |
Binding | Hardcover |
ItemPartNumber | 93 black & white illustrations, 32 black |
UnitCount | 1 |
Format | Illustrated |
EANs | 9781482241396 |
ReleaseDate | 0000-00-00 |