國立高雄大學圖資館 |

登入

回首頁

Distributed machine learning and computingtheory and applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Distributed machine learning and computingedited by M. Hadi Amini.
其他題名:	theory and applications /
其他作者:	Amini, M. Hadi.
出版者:	Cham :Springer International Publishing :2024.
面頁冊數:	x, 158 p. :ill. (chiefly col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Machine learning.
電子資源:	https://doi.org/10.1007/978-3-031-57567-9
ISBN:	9783031575679$q(electronic bk.)

Distributed machine learning and computingtheory and applications /
Distributed machine learning and computingtheory and applications /[electronic resource] :edited by M. Hadi Amini. - Cham :Springer International Publishing :2024. - x, 158 p. :ill. (chiefly col.), digital ;24 cm. - Big and integrated artificial intelligence,v. 22662-4141 ;. - Big and integrated artificial intelligence ;v. 1..

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.

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.

ISBN: 9783031575679$q(electronic bk.)

Standard No.: 10.1007/978-3-031-57567-9doiSubjects--Topical Terms:

188639
Machine learning.

LC Class. No.: Q325.5 / .D57 2024

Dewey Class. No.: 006.31

Distributed machine learning and computingtheory and applications /
LDR:02579nmm a2200337 a 4500 001 659258
003 DE-He213
005 20240529103950.0
006 m d
007 cr nn 008maaau
008 240927s2024 sz s 0 eng d
020 $a 9783031575679$q(electronic bk.)
020 $a 9783031575662$q(paper)
024 7 $a 10.1007/978-3-031-57567-9 $2 doi
035 $a 978-3-031-57567-9
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5 $b .D57 2024
072 7 $a TJK $2 bicssc
072 7 $a TEC041000 $2 bisacsh
072 7 $a TJK $2 thema
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .D614 2024
245 0 0 $a Distributed machine learning and computing $h [electronic resource] : $b theory and applications / $c edited by M. Hadi Amini.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2024.
300 $a x, 158 p. : $b ill. (chiefly col.), digital ; $c 24 cm.
490 1 $a Big and integrated artificial intelligence, $x 2662-4141 ; $v v. 2
505 0 $a 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.
520 $a 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.
650 0 $a Machine learning. $3 188639
650 0 $a Distributed artificial intelligence. $3 266670
650 1 4 $a Communications Engineering, Networks. $3 273745
650 2 4 $a Computational Intelligence. $3 338479
650 2 4 $a Machine Learning. $3 833608
650 2 4 $a Cyber-Physical Systems. $3 919034
700 1 $a Amini, M. Hadi. $3 770483
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Big and integrated artificial intelligence ; $v v. 1. $3 922371
856 4 0 $u https://doi.org/10.1007/978-3-031-57567-9
950 $a Engineering (SpringerNature-11647)