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Proceedings of ELM 2018 - Proceedings in Adaptation, Learning and Optimization 2020 edition
Proceedings of ELM 2018 - 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.
347 pages, 100 Tables, color; 79 Illustrations, color; 30 Illustrations, black and white; VIII, 347
| Medios de comunicación | Libros Paperback Book (Libro con tapa blanda y lomo encolado) |
| Publicado | 15 de agosto de 2020 |
| ISBN13 | 9783030233099 |
| Editores | Springer Nature Switzerland AG |
| Páginas | 347 |
| Dimensiones | 150 × 220 × 10 mm · 498 g |
| Lengua | Alemán |
| Editor | Cao, Jiuwen |
| Editor | Lendasse, Amaury |
| Editor | Miche, Yoan |
| Editor | Vong, Chi Man |