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First-order and Stochastic Optimization Methods for Machine Learning - Springer Series in the Data Sciences Guanghui Lan 2020 edition
First-order and Stochastic Optimization Methods for Machine Learning - Springer Series in the Data Sciences
Guanghui Lan
This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms.
582 pages, 12 Tables, color; 16 Illustrations, color; 2 Illustrations, black and white; XIII, 582 p.
| メディア | 書籍 Hardcover Book (ハードカバー付きの本) |
| リリース済み | 2020年5月16日 |
| ISBN13 | 9783030395674 |
| 出版社 | Springer Nature Switzerland AG |
| ページ数 | 582 |
| 寸法 | 243 × 161 × 40 mm · 1,02 kg |
| 言語 | ドイツ語 |