Xiangjie Kong - Böcker
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4 produkter
4 produkter
Del 616 - Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Applied Computational Intelligence, Informatics and Big Data
First International Conference, ACIIBD 2024, Guangzhou, China, July 26–28, 2024, Proceedings
Häftad, Engelska, 2025
987 kr
Skickas inom 10-15 vardagar
This Proceedings cover topics on Internet of Things, Information Communication Technology, Edge Computing, Mobile Computing, Neural Network, Intelligent Control System, Real-Time Information System, Intelligent Perception and many other cutting-edge fields and disciplines.
Visual Object Tracking across Modalities
Foundations, Methods, and Future Directions
Inbunden, Engelska, 2026
1 892 kr
Skickas inom 10-15 vardagar
1 314 kr
Skickas inom 7-10 vardagar
This book introduces the prevailing domains of recommender systems and cross-device federated learning, highlighting the latest research progress and prospects regarding cross-device federated recommendation.
1 314 kr
Skickas inom 10-15 vardagar
This book introduces the prevailing domains of recommender systems and cross-device federated learning, highlighting the latest research progress and prospects regarding cross-device federated recommendation. As a privacy-oriented distributed computing paradigm, cross-device federated learning enables collaborative intelligence across multiple devices while ensuring the security of local data. In this context, ubiquitous recommendation services emerge as a crucial application of device-side AI, making a deep exploration of federated recommendation systems highly significant.This book is self-contained, and each chapter can be comprehended independently. Overall, the book organizes existing efforts in federated recommendation from three different perspectives. The perspective of learning paradigms includes statistical machine learning, deep learning, reinforcement learning, and meta learning, where each has detailed techniques (e.g., different neural building blocks) to present relevant studies. The perspective of privacy computing covers homomorphic encryption, differential privacy, secure multi-party computing, and malicious attacks. More specific encryption and obfuscation techniques, such as randomized response and secret sharing, are involved. The perspective of federated issues discusses communication optimization and fairness perception, which are widely concerned in the cross-device distributed environment. In the end, potential issues and promising directions for future research are identified point by point.This book is especially suitable for researchers working on the application of recommendation algorithms to the privacy-preserving federated scenario. The target audience includes graduate students, academic researchers, and industrial practitioners who specialize in recommender systems, distributed machine learning, information retrieval, information security, or artificial intelligence.