Proceedings of the 10th International Conference on Advanced Intelligent Systems and Informatics 2024 PDF Download
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Author: Aboul Ella Hassanien
Publisher: Springer Nature
ISBN: 3031716191
Category :
Languages : en
Pages : 403
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Book Description
Author: Aboul Ella Hassanien
Publisher: Springer Nature
ISBN: 3031716191
Category :
Languages : en
Pages : 403
Get Book Here
Book Description
Author: Lin Zhang
Publisher: Springer Nature
ISBN: 9819739489
Category :
Languages : en
Pages : 295
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Book Description
Author: Prasant Kumar Pattnaik
Publisher: Springer Nature
ISBN: 9819705738
Category :
Languages : en
Pages : 642
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Book Description
Author: Luca Longo
Publisher: Springer Nature
ISBN: 3031637879
Category :
Languages : en
Pages : 508
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Book Description
Author: Zhengbing Hu
Publisher: Springer Nature
ISBN: 3031361156
Category : Technology & Engineering
Languages : en
Pages : 1107
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Book Description
This book comprises high-quality refereed research papers presented at the 3rd International Conference on Artificial Intelligence and Logistics Engineering (ICAILE2023), held in Wuhan, China, on March 11–12, 2023, organized jointly by Wuhan University of Technology, Nanning University, the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Huazhong University of Science and Technology, the Polish Operational and Systems Society, Wuhan Technology and Business University, and the International Research Association of Modern Education and Computer Science. The topics discussed in the book include state-of-the-art papers in artificial intelligence and logistics engineering. It is an excellent source of references for researchers, graduate students, engineers, management practitioners, and undergraduate students interested in artificial intelligence and its applications in logistics engineering.
Author:
Publisher:
ISBN: 9781665498685
Category :
Languages : en
Pages : 0
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Book Description
Author: Abbas Moallem
Publisher: Springer Nature
ISBN: 3031613791
Category :
Languages : en
Pages : 336
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Book Description
Author: Charu C. Aggarwal
Publisher: Springer
ISBN: 3319296590
Category : Computers
Languages : en
Pages : 518
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Book Description
This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases. Recommender system methods have been adapted to diverse applications including query log mining, social networking, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three categories: Algorithms and evaluation: These chapters discuss the fundamental algorithms in recommender systems, including collaborative filtering methods, content-based methods, knowledge-based methods, ensemble-based methods, and evaluation. Recommendations in specific domains and contexts: the context of a recommendation can be viewed as important side information that affects the recommendation goals. Different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored. Advanced topics and applications: Various robustness aspects of recommender systems, such as shilling systems, attack models, and their defenses are discussed. In addition, recent topics, such as learning to rank, multi-armed bandits, group systems, multi-criteria systems, and active learning systems, are introduced together with applications. Although this book primarily serves as a textbook, it will also appeal to industrial practitioners and researchers due to its focus on applications and references. Numerous examples and exercises have been provided, and a solution manual is available for instructors.
Author: Kenneth David Strang
Publisher:
ISBN: 9781466656277
Category : Contingency theory (Management)
Languages : en
Pages : 106
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Book Description
Author: Qiang Yang
Publisher: Springer Nature
ISBN: 3030630765
Category : Computers
Languages : en
Pages : 291
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Book Description
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.”
