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Federated and Transfer Learning - Adaptation, Learning, and Optimization 1st ed. 2023 edition
Federated and Transfer Learning - Adaptation, Learning, and Optimization
This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated learning as well as its connection with transfer learning and reinforcement learning.
371 pages, 80 Illustrations, color; 10 Illustrations, black and white; VIII, 371 p. 90 illus., 80 il
| 介质类型 | 图书 Hardcover Book (精装硬皮书) |
| 已发行 | 2022年10月1日 |
| ISBN13 | 9783031117473 |
| 出版商 | Springer International Publishing AG |
| 页数 | 371 |
| 商品尺寸 | 150 × 220 × 20 mm · 735 g |
| 语言 | 德语 |
| 编辑 | Razavi-Far, Roozbeh |
| 编辑 | Taylor, Matthew E. |
| 编辑 | Wang, Boyu |
| 编辑 | Yang, Qiang |