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Proceedings of ELM-2017 - Proceedings in Adaptation, Learning and Optimization Softcover Reprint of the Original 1st 2019 edition
Proceedings of ELM-2017 - Proceedings in Adaptation, Learning and Optimization
ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series,etc) as long as they are nonlinear piecewise continuous, independent of training data and application environments.
340 pages, 130 Illustrations, black and white; VII, 340 p. 130 illus.
| Medios de comunicación | Libros Paperback Book (Libro con tapa blanda y lomo encolado) |
| Publicado | 10 de diciembre de 2019 |
| ISBN13 | 9783030131821 |
| Editores | Springer Nature Switzerland AG |
| Páginas | 340 |
| Dimensiones | 150 × 220 × 10 mm · 534 g |
| Lengua | Alemán |
| Editor | Cao, Jiuwen |
| Editor | Lendasse, Amaury |
| Editor | Miche, Yoan |
| Editor | Vong, Chi Man |