Federated Learning, Yang, Qiang Liu, Yang Cheng, Yong Kang, Yan Chen, Tianjian Yu, Han
Автор: Rehman Название: Federated Learning Systems ISBN: 3030706060 ISBN-13(EAN): 9783030706067 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Federated learning enables the distribution of the learning models across the devices and systems which perform initial training and report the updated model attributes to the centralized cloud servers for secure and privacy-preserving attribute aggregation and global model development.
Автор: Gaurav Dhiman, Sandeep Kautish Название: Demystifying Federated Learning for Blockchain and Industrial Internet of Things ISBN: 1668437333 ISBN-13(EAN): 9781668437339 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 280890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Rediscovers, redefines, and reestablishes the most recent applications of federated learning using blockchain and IIoT to optimize data for next-generation networks. The book provides insights to readers in a way of inculcating the theme that shapes the next generation of secure communication.
Автор: Gaurav Dhiman, Sandeep Kautish Название: Demystifying Federated Learning for Blockchain and Industrial Internet of Things ISBN: 1668437341 ISBN-13(EAN): 9781668437346 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 212520.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Rediscovers, redefines, and reestablishes the most recent applications of federated learning using blockchain and IIoT to optimize data for next-generation networks. The book provides insights to readers in a way of inculcating the theme that shapes the next generation of secure communication.
Автор: Adria Gascon, Aleksandra Korolova, Ananda Theertha Suresh, Arjun Nitin Bhagoji, Aurelien Bellet, Ayfer Ozgur, Badih Ghazi, Ben Hutchinson, Brendan Ave Название: Advances and Open Problems in Federated Learning ISBN: 1680837885 ISBN-13(EAN): 9781680837889 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 91470.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The term Federated Learning was coined as recently as 2016 to describe a machine learning setting where multiple entities collaborate in solving a machine learning problem, under the coordination of a central server or service provider. This book describes the latest state-of-the art.
Автор: Hong Choong Seon, Khan Latif U., Chen Mingzhe Название: Federated Learning for Wireless Networks ISBN: 9811649626 ISBN-13(EAN): 9789811649622 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: It is divided into three main parts: The first part briefly discusses the fundamentals of FL for wireless networks, while the second part comprehensively examines the design and analysis of wireless FL, covering resource optimization, incentive mechanism, security and privacy.
Автор: Verma Dinesh C. Название: Federated AI for Real-World Business Scenarios ISBN: 0367861577 ISBN-13(EAN): 9780367861575 Издательство: Taylor&Francis Рейтинг: Цена: 153120.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides a holistic overview of all aspects of federated AI, which allows creation of real-world applications in contexts where data is dispersed in many different locations.
Modeling and analyzing resource-sensitive actors: A tutorial introduction.- Manifestly Phased Communication via Shared Session Types.- Deconfined Global Types for Asynchronous Sessions.- Relating Functional and Imperative Session Types.- Safe Session-Based Asynchronous Coordination in Rust.- A Session Subtyping Tool.- Towards Probabilistic Session-Type Monitoring.- Java Typestate Checker.- Asynchronous Global Types in co-logic Programming.- Tuple-Based Coordination in Large-Scale Situated Systems.- A Theory of Automated Market Makers in DeFi.- ReGraDa: Reactive Graph Data.- The Structure of Concurrent Process Histories.- A Clean and Efficient Implementation of Choreography Synthesis for Behavioural Contracts.- A Practical Tool-Chain for the Development of Coordination Scenarios: Graphical Modeler, DSL, Code Generators and Automaton-Based Simulator.- Microservice Dynamic Architecture-Level Deployment Orchestration.- Jolie & LEMMA: Model-Driven Engineering and Programming Languages Meet on Microservices.- ScaFi-Web: a Web-Based Application for Field-Based Coordination Programming.
Автор: Rehman Muhammad Habib Ur, Gaber Mohamed Medhat Название: Federated Learning Systems: Towards Next-Generation AI ISBN: 3030706036 ISBN-13(EAN): 9783030706036 Издательство: Springer Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Federated learning enables the distribution of the learning models across the devices and systems which perform initial training and report the updated model attributes to the centralized cloud servers for secure and privacy-preserving attribute aggregation and global model development.
Автор: Yang Qiang, Fan Lixin, Yu Han Название: Federated Learning: Privacy and Incentive ISBN: 3030630757 ISBN-13(EAN): 9783030630751 Издательство: Springer Цена: 69870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications.
Автор: Bliudze Simon, Bocchi Laura Название: Coordination Models and Languages: 22nd Ifip Wg 6.1 International Conference, Coordination 2020, Held as Part of the 15th International Federated Conf ISBN: 3030500284 ISBN-13(EAN): 9783030500283 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the proceedings of the 22nd International Conference on Coordination Models and Languages, COORDINATION 2020, which was due to be held in Valletta, Malta, in June 2020, as part of the 15th International Federated Conference on Distributed Computing Techniques, DisCoTec 2020.
Автор: Gao Wanling, Hwang Kai, Wang Changyun Название: Intelligent Computing and Block Chain: First Benchcouncil International Federated Conferences, Ficc 2020, Qingdao, China, October 30 - November 3, 202 ISBN: 9811611599 ISBN-13(EAN): 9789811611599 Издательство: Springer Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed post-conference proceedings of the Second BenchCouncil International Federated Intelligent Computing and Block Chain Conferences, FICC 2020, held in Qingdao, China, in October/ November 2020.The 32 full papers and 6 short papers presented were carefully reviewed and selected from 103 submissions.
Автор: Qiang Yang, Yang Liu, Yong Cheng, Yan Kang, Tianjian Chen, Han Yu Название: Federated Learning ISBN: 1681736977 ISBN-13(EAN): 9781681736976 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 82230.00 T Наличие на складе: Нет в наличии. Описание: How is it possible to allow multiple data owners to collaboratively train and use a shared prediction model while keeping all the local training data private? Traditional machine learning approaches need to combine all data at one location, typically a data center, which may very well violate the laws on user privacy and data confidentiality. Today, many parts of the world demand that technology companies treat user data carefully according to user-privacy laws. The European Union's General Data Protection Regulation (GDPR) is a prime example. In this book, we describe how federated machine learning addresses this problem with novel solutions combining distributed machine learning, cryptography and security, and incentive mechanism design based on economic principles and game theory. We explain different types of privacy-preserving machine learning solutions and their technological backgrounds, and highlight some representative practical use cases. We show how federated learning can become the foundation of next-generation machine learning that caters to technological and societal needs for responsible AI development and application.
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