Federated Learning

丛 书 名：Machine Learning: Foundations, Methodologies, and Applications

版本说明：1

作     者：Yaochu Jin Hangyu Zhu Jinjin Xu Yang Chen 

I S B N：(纸本) 9789811970825;9789811970856 

出 版 社：Springer Singapore 

出 版 年：1000年

页      数：XI, 218页

主 题 词：Machine Learning Privacy Cryptology 

摘      要：The book starts with a self-contained introduction to artificial neural networks, deep learning models, supervised learning algorithms, evolutionary algorithms, and evolutionary learning. Concise information is then presented on multi-party secure computation, differential privacy, and homomorphic encryption, followed by a detailed description of federated learning. In turn, the book addresses the latest advances in federate learning research, especially from the perspectives of communication efficiency, evolutionarylearning, and privacy preservation.;The book is particularly well suited for graduate students, academic researchers, and industrial practitioners in the field of machine learning and artificial intelligence. It can also be used as a self-learning resource for readers with a science or engineering background, or as a reference text for graduate courses.