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Accelerated Optimization for Machine Learning: First-Order Algorithms Zhouchen Lin 2020 edition
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Accelerated Optimization for Machine Learning: First-Order Algorithms
Zhouchen Lin
The acceleration of first-order optimization algorithms is crucial for the efficiency of machine learning. Written by leading experts in the field, this book provides a comprehensive introduction to, and state-of-the-art review of accelerated first-order optimization algorithms for machine learning.
275 pages, 36 Illustrations, black and white; XXIV, 275 p. 36 illus.
| Media | Bøker Innbunden bok (Bok med hard rygg og stivt omslag) |
| Utgitt | 30. mai 2020 |
| ISBN13 | 9789811529092 |
| Utgivere | Springer Verlag, Singapore |
| Antall sider | 275 |
| Mål | 150 × 220 × 20 mm · 639 g |
![Cover for Zhouchen Lin · Alternating Direction Method of Multipliers for Machine Learning (Innbunden bok) [2022 edition] (2022)](https://imusic.b-cdn.net/images/item/original/392/9789811698392.jpg?zhouchen-lin-2022-alternating-direction-method-of-multipliers-for-machine-learning-innbunden-bok&class=scaled&v=1654990678)