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Proceedings of ELM 2018 1st ed. 2020 edition
Proceedings of ELM 2018
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 Book |
| Publicado | 30 de junio de 2019 |
| ISBN13 | 9783030233068 |
| Editores | Springer Nature Switzerland AG |
| Páginas | 347 |
| Dimensiones | 150 × 220 × 20 mm · 671 g |
| Lengua | Alemán |
| Editor | Cao, Jiuwen |
| Editor | Lendasse, Amaury |
| Editor | Miche, Yoan |
| Editor | Vong, Chi Man |