Federated Learning: Theory and Practice
Nguyen, Lam M., Hoang, Trong Nghia, Chen, Pin-Yu
- 出版商: Academic Press
- 出版日期: 2024-02-15
- 售價: $4,290
- 貴賓價: 9.5 折 $4,076
- 語言: 英文
- 頁數: 434
- 裝訂: Quality Paper - also called trade paper
- ISBN: 0443190372
- ISBN-13: 9780443190377
-
相關分類:
Machine Learning
海外代購書籍(需單獨結帳)
買這商品的人也買了...
-
Federated Learning Systems: Towards Next-Generation AI$7,030$6,679 -
Federated Learning with Python: Design and implement a federated learning system and develop applications using existing frameworks$1,700$1,615 -
Federated Learning for Wireless Networks$7,030$6,679 -
Federated Learning for Internet of Medical Things: Concepts, Paradigms, and Solutions$5,530$5,254 -
Federated Learning: A Comprehensive Overview of Methods and Applications$7,030$6,679 -
Federated Learning for Future Intelligent Wireless Networks$5,120$4,864 -
Handbook on Federated Learning: Advances, Applications and Opportunities$7,030$6,679 -
Federated AI for Real-World Business Scenarios$2,800$2,660 -
Security and Privacy in Federated Learning$7,180$6,821 -
Communication Efficient Federated Learning for Wireless Networks$6,650$6,318 -
Adversarial Multimedia Forensics$7,770$7,382 -
The Potential of Generative AI: Transforming Technology, Business and Art Through Innovative AI Applications$1,670$1,587 -
Privacy-Preserving Machine Learning: A use-case-driven approach to building and protecting ML pipelines from privacy and security threats$1,800$1,710 -
Artificial Intelligence for Smart Manufacturing: Methods, Applications, and Challenges$6,800$6,460 -
Unleashing the Power of Data with Trusted AI: A guide for board members and executives$4,020$3,819 -
Security and Risk Analysis for Intelligent Edge Computing$7,940$7,543 -
Industrial Edge Computing: Architecture, Optimization and Applications$7,770$7,382 -
Mobile and Ubiquitous Systems: Computing, Networking and Services: 20th Eai International Conference, Mobiquitous 2023, Melbourne, Vic, Australia, Nov$4,040$3,838 -
LLM Model Security: Strategies, Best Practices, and Future Trends$1,050$998 -
LLM and Generative AI for Healthcare: A Comprehensive Guide$1,050$998 -
Generative AI Strategy and Implementation: Mastering Techniques and Advanced Applications$850$808 -
Generative AI Transformation: A Guide for Everyone$970$922 -
Generative AI for Manufacturing$2,220$2,109 -
Generative AI for Robotics and Autonomous Systems$2,300$2,185 -
Learn Python Generative AI: Journey from autoencoders to transformers to large language models (English Edition)$1,700$1,615
商品描述
Federated Learning: Theory and Practi ce provides a holisti c treatment to federated learning as a distributed learning system with various forms of decentralized data and features. Part I of the book begins with a broad overview of opti mizati on fundamentals and modeling challenges, covering various aspects of communicati on effi ciency, theoretical convergence, and security. Part II features
emerging challenges stemming from many socially driven concerns of federated learning as a future public machine learning service. Part III concludes the book with a wide array of industrial applicati ons of federated learning, as well as ethical considerations, showcasing its immense potential for driving innovation while safeguarding sensitive data.
Federated Learning: Theory and Practi ce provides a comprehensive and accessible introducti on to federated learning which is suitable for researchers and students in academia, and industrial practitioners who seek to leverage the latest advance in machine learning for their entrepreneurial endeavors.
