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Proceedings of ELM 2017 1st ed. 2019 edition
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Proceedings of ELM 2017
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.
| Media | Boeken Book |
| Vrijgegeven | 17 oktober 2018 |
| ISBN13 | 9783030015190 |
| Uitgevers | Springer Nature Switzerland AG |
| Pagina's | 340 |
| Afmetingen | 150 × 220 × 20 mm · 688 g |
| Taal en grammatica | Duits |
| Uitgever | Cao, Jiuwen |
| Uitgever | Lendasse, Amaury |
| Uitgever | Miche, Yoan |
| Uitgever | Vong, Chi Man |
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