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商品詳細
Learning Representation for Multi-View Data Analysis: Models and Applications. 2019 ed.
・ISBN 978-3-030-00733-1 hard EUR 129.99
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お気に入り
★★★
| 著者・編者 | Ding, Zhengming / Zhao, Handong / Fu, Yun, |
|---|---|
| シリーズ | (Advanced Information and Knowledge Processing) |
| 出版社 | (Springer Nature Switzerland AG, SZ) |
| 出版年月 | 2018 |
| ページ数 | 268 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A02-20172＞ |
解説
This book equips readers to handle complex multi-view data representation, centered around several major visual applications, sharing many tips and insights through a unified learning framework. This framework is able to model most existing multi-view learning and domain adaptation, enriching readers' understanding from their similarity, and differences based on data organization and problem settings, as well as the research goal.
A comprehensive review exhaustively provides the key recent research on multi-view data analysis, i.e., multi-view clustering, multi-view classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.