株式会社極東書店トップ ＞ 商品一覧 ＞ Intelligent Data Engineering and Automated Learning - IDEAL 2023: 24th International Conference, Evora, Portugal, November 22-24, 2023, Proceedings. 1st ed. 2023
商品詳細
Intelligent Data Engineering and Automated Learning - IDEAL 2023: 24th International Conference, Evora, Portugal, November 22-24, 2023, Proceedings. 1st ed. 2023
・ISBN 978-3-031-48231-1 paper EUR 81.99
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| 著者・編者 | Quaresma, Paulo / Camacho, David / Yin, Hujun / Goncalves, Teresa / Julian, Vicente / Tallon-Ballesteros, Antonio J. (eds.), |
|---|---|
| シリーズ | (Lecture Notes in Computer Science) |
| 出版社 | (Springer International Publishing AG, SZ) |
| 出版年月 | 2023 |
| ページ数 | 549 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A01-88797＞ |
解説
This book constitutes the proceedings of the 24th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2023, held in Evora, Portugal, during November 22-24, 2023.
The 45 full papers and 4 short papers presented in this book were carefully reviewed and selected from 77 submissions. IDEAL 2023 is focusing on big data challenges, machine learning, deep learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models, agents and hybrid intelligent systems, and real-world applications of intelligence techniques and AI.
The papers are organized in the following topical sections: main track; special session on federated learning and (pre) aggregation in machine learning; special session on intelligent techniques for real-world applications of renewable energy and green transport; and special session on data selection in machine learning.
The 45 full papers and 4 short papers presented in this book were carefully reviewed and selected from 77 submissions. IDEAL 2023 is focusing on big data challenges, machine learning, deep learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models, agents and hybrid intelligent systems, and real-world applications of intelligence techniques and AI.
The papers are organized in the following topical sections: main track; special session on federated learning and (pre) aggregation in machine learning; special session on intelligent techniques for real-world applications of renewable energy and green transport; and special session on data selection in machine learning.