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Distributed Machine Learning and Computing : Theory and Applications / edited by M. Hadi Amini

Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Big and Integrated Artificial Intelligence ; 2Publisher: Cham : Springer International Publishing, 2024Publisher: Cham : Imprint: Springer, 2024Edition: 1st ed. 2024Description: 1 Online-Ressource(X, 158 p. 29 illus., 28 illus. in color.)ISBN:
  • 9783031575679
Subject(s): Additional physical formats: 9783031575662 | 9783031575686 | 9783031575693 | Erscheint auch als: 9783031575662 Druck-Ausgabe | Erscheint auch als: 9783031575686 Druck-Ausgabe | Erscheint auch als: 9783031575693 Druck-AusgabeDOI: DOI: 10.1007/978-3-031-57567-9Online resources: Summary: Chapter 1. Distributed Machine Learning and Computing: An Overview -- Chapter 2. Distributed Multi-agent Meta Learning for Trajectory Design in Wireless Drone Networks -- Chapter 3. Heterogeneity Aware Distributed Machine Learning at the Wireless Edge for Health IoT Applications: An EEG Data Case Study -- Chapter 4. A Comprehensive Review of Artificial Intelligence and Machine Learning Methods for Modern Health-care Systems -- Chapter 5. Vertical Federated Learning: Principles, Applications, and Future Frontiers -- Chapter 6. Decentralization of Energy Systems with Blockchain: Bridging Top-down and Bottom-up Management of the Electricity Grid.-Chapter 7. Empowering Distributed Solutions in Renewable Energy Systems and Grid Optimization.Summary: This book focuses on a wide range of distributed machine learning and computing algorithms and their applications in healthcare and engineering systems. The contributors explore how these techniques can be applied to different real-world problems. It is suitable for students and researchers interested in conducting research in multidisciplinary areas that rely on distributed machine learning and computing techniques. Specifies the value of efficient theoretical methods in dealing with large-scale decision-making problems; Provides an investigation of distributed machine learning and optimization algorithms for large-scale networks; Includes basics and mathematical foundations needed to analyze and address the interdependent complex networks.PPN: PPN: 1890575518Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-ENG | ZDB-2-SXE
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