Federated Learning A Systematic Review
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Federated Learning A Systematic Review
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Author :
language : en
Publisher: BoD – Books on Demand
Release Date : 2025-04-02
Federated Learning A Systematic Review written by and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-02 with Computers categories.
Federated Learning (FL) represents a transformative leap in distributed machine learning by enabling multiple clients to collaboratively solve complex tasks without compromising data privacy. This innovative approach eliminates the need for centralized cloud storage, ensuring privacy-preserving data handling while offering smarter models, reduced latency, and enhanced power efficiency. This book serves as a comprehensive guide to the evolving field of Federated Learning, providing in-depth insights into its definition, architecture, and classification. It examines the distinctions between FL and traditional distributed learning paradigms through a comparative lens. The chapters explore key concepts, algorithmic advancements, and computational strategies that underpin the development of FL, with a particular focus on deep learning applications. Readers will find detailed discussions on critical topics such as horizontal and vertical FL, federated neural networks, federated reinforcement learning, and specialized algorithms like Federated LSTM and CNNs. By bridging theoretical foundations with practical implementations, the book also addresses common challenges in FL and presents potential pathways for future advancements. Aimed at researchers, academics, and practitioners, this book is valuable for understanding Federated Learning's role in shaping the future of privacy-conscious, intelligent machine learning systems.
Federated Learning Systems
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Author : Muhammad Habib ur Rehman
language : en
Publisher: Springer Nature
Release Date : 2021-06-11
Federated Learning Systems written by Muhammad Habib ur Rehman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-11 with Technology & Engineering categories.
This book covers the research area from multiple viewpoints including bibliometric analysis, reviews, empirical analysis, platforms, and future applications. The centralized training of deep learning and machine learning models not only incurs a high communication cost of data transfer into the cloud systems but also raises the privacy protection concerns of data providers. This book aims at targeting researchers and practitioners to delve deep into core issues in federated learning research to transform next-generation artificial intelligence applications. 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. Federated learning benefits in terms of privacy, communication efficiency, data security, and contributors’ control of their critical data.
Federated Learning
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Author : Qiang Yang
language : en
Publisher: Springer Nature
Release Date : 2020-11-25
Federated Learning written by Qiang Yang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-25 with Computers categories.
This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book. It is timely as federated learning is becoming popular after the release of the General Data Protection Regulation (GDPR). Since federated learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. Firstly, it introduces different privacy-preserving methods for protecting a federated learning model against different types of attacks such as data leakage and/or data poisoning. Secondly, the book presents incentive mechanisms which aim to encourage individuals to participate in the federated learning ecosystems. Last but not least, this book also describes how federated learning can be applied in industry and business to address data silo and privacy-preserving problems. The book is intended for readers from both the academia and the industry, who would like to learn about federated learning, practice its implementation, and apply it in their own business. Readers are expected to have some basic understanding of linear algebra, calculus, and neural network. Additionally, domain knowledge in FinTech and marketing would be helpful.”
Handbook On Federated Learning
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Author : Saravanan Krishnan
language : en
Publisher: CRC Press
Release Date : 2024-01-09
Handbook On Federated Learning written by Saravanan Krishnan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-09 with Computers categories.
Mobile, wearable, and self-driving telephones are just a few examples of modern distributed networks that generate enormous amount of information every day. Due to the growing computing capacity of these devices as well as concerns over the transfer of private information, it has become important to process the part of the data locally by moving the learning methods and computing to the border of devices. Federated learning has developed as a model of education in these situations. Federated learning (FL) is an expert form of decentralized machine learning (ML). It is essential in areas like privacy, large-scale machine education and distribution. It is also based on the current stage of ICT and new hardware technology and is the next generation of artificial intelligence (AI). In FL, central ML model is built with all the data available in a centralised environment in the traditional machine learning. It works without problems when the predictions can be served by a central server. Users require fast responses in mobile computing, but the model processing happens at the sight of the server, thus taking too long. The model can be placed in the end-user device, but continuous learning is a challenge to overcome, as models are programmed in a complete dataset and the end-user device lacks access to the entire data package. Another challenge with traditional machine learning is that user data is aggregated at a central location where it violates local privacy policies laws and make the data more vulnerable to data violation. This book provides a comprehensive approach in federated learning for various aspects.
Intersection Of Artificial Intelligence Data Science And Cutting Edge Technologies From Concepts To Applications In Smart Environment
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Author : Yousef Farhaoui
language : en
Publisher: Springer Nature
Release Date : 2025-06-30
Intersection Of Artificial Intelligence Data Science And Cutting Edge Technologies From Concepts To Applications In Smart Environment written by Yousef Farhaoui and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-30 with Computers categories.
Offering a comprehensive exploration, this book navigates through foundational concepts to advanced applications, providing readers with a holistic understanding of how these domains intersect to create intelligent and responsive environments. The Intersection of Artificial Intelligence, Data Science, and Cutting-Edge Technologies: From Concepts to Applications in Smart Environments delves into the convergence of AI, data science, and innovative technologies within the realm of smart environments. Through a blend of theoretical insights and practical examples, the book illuminates the synergies between AI and data science, showcasing their pivotal roles in shaping the future of smart environments. From sensor technologies to machine learning algorithms, the text elucidates the mechanisms driving intelligence in these environments, while also delving into the ethical considerations and societal impacts of deploying such technologies. Whether you're a researcher, practitioner, or enthusiast in the fields of AI, data science, or smart environments, this book serves as a guiding beacon, offering valuable insights and methodologies to navigate the complexities of creating and optimizing intelligent environments for the benefit of society.
Neural Information Processing
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Author : Mufti Mahmud
language : en
Publisher: Springer Nature
Release Date : 2025-06-24
Neural Information Processing written by Mufti Mahmud and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-24 with Computers categories.
The sixteen-volume set, CCIS 2282-2297, constitutes the refereed proceedings of the 31st International Conference on Neural Information Processing, ICONIP 2024, held in Auckland, New Zealand, in December 2024. The 472 regular papers presented in this proceedings set were carefully reviewed and selected from 1301 submissions. These papers primarily focus on the following areas: Theory and algorithms; Cognitive neurosciences; Human-centered computing; and Applications.
Data Driven Evolutionary Optimization
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Author : Yaochu Jin
language : en
Publisher: Springer Nature
Release Date : 2021-06-28
Data Driven Evolutionary Optimization written by Yaochu Jin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-28 with Computers categories.
Intended for researchers and practitioners alike, this book covers carefully selected yet broad topics in optimization, machine learning, and metaheuristics. Written by world-leading academic researchers who are extremely experienced in industrial applications, this self-contained book is the first of its kind that provides comprehensive background knowledge, particularly practical guidelines, and state-of-the-art techniques. New algorithms are carefully explained, further elaborated with pseudocode or flowcharts, and full working source code is made freely available. This is followed by a presentation of a variety of data-driven single- and multi-objective optimization algorithms that seamlessly integrate modern machine learning such as deep learning and transfer learning with evolutionary and swarm optimization algorithms. Applications of data-driven optimization ranging from aerodynamic design, optimization of industrial processes, to deep neural architecture search are included.
Hci International 2023 Late Breaking Papers
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Author : Helmut Degen
language : en
Publisher: Springer Nature
Release Date : 2023-11-25
Hci International 2023 Late Breaking Papers written by Helmut Degen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-25 with Computers categories.
This seven-volume set LNCS 14054-14060 constitutes the proceedings of the 25th International Conference, HCI International 2023, in Copenhagen, Denmark, in July 2023. For the HCCII 2023 proceedings, a total of 1578 papers and 396 posters was carefully reviewed and selected from 7472 submissions. Additionally, 267 papers and 133 posters are included in the volumes of the proceedings published after the conference, as “Late Breaking Work”. These papers were organized in the following topical sections: HCI Design and User Experience; Cognitive Engineering and Augmented Cognition; Cultural Issues in Design; Technologies for the Aging Population; Accessibility and Design for All; Designing for Health and Wellbeing; Information Design, Visualization, Decision-making and Collaboration; Social Media, Creative Industries and Cultural Digital Experiences; Digital Human Modeling, Ergonomics and Safety; HCI in Automated Vehicles and Intelligent Transportation; Sustainable GreenSmart Cities and Smart Industry; eXtended Reality Interactions; Gaming and Gamification Experiences; Interacting with Artificial Intelligence; Security, Privacy, Trust and Ethics; Learning Technologies and Learning Experiences; eCommerce, Digital Marketing and eFinance.
Proceedings Of International Conference On Information Technology And Applications
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Author : Abrar Ullah
language : en
Publisher: Springer Nature
Release Date : 2025-06-14
Proceedings Of International Conference On Information Technology And Applications written by Abrar Ullah and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-14 with Computers categories.
This book includes high-quality papers presented at 18th International Conference on Information Technology and Applications (ICITA 2024), held in Sydney, Australia, during October 17–19, 2024. The book presents original research work of academics and industry professionals to exchange their knowledge of the state-of-the-art research and development in information technology and applications. The topics covered in the book are cloud computing, business process engineering, machine learning, evolutionary computing, big data analytics, internet of things and cyber-physical systems, information and knowledge management, computer vision and image processing, computer graphics and games programming, mobile computing, ontology engineering, software and systems modeling, human computer interaction, online learning /e-learning, computer networks, and web engineering.
Innovative Computing And Communications
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Author : Aboul Ella Hassanien
language : en
Publisher: Springer Nature
Release Date : 2024-10-14
Innovative Computing And Communications written by Aboul Ella Hassanien and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-14 with Technology & Engineering categories.
This book includes high-quality research papers presented at the Seventh International Conference on Innovative Computing and Communication (ICICC 2024), which is held at the Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India, on 16–17 February 2024. Introducing the innovative works of scientists, professors, research scholars, students, and industrial experts in the field of computing and communication, the book promotes the transformation of fundamental research into institutional and industrialized research and the conversion of applied exploration into real-time applications.