Edge-Cloud Computing and Federated-Split Learning in the Internet of Things

Federated Learning (FL) is a new collaborative learning method that allows multiple data owners to cooperate in ML model training without exposing private data. Split Learning (SL) is an emerging collaborative learning method that splits an ML model into multiple portions that are trained collaborat...

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Médium:	E-kniha
Jazyk:	angličtina
Vydáno:	Basel MDPI - Multidisciplinary Digital Publishing Institute 2024
Témata:	accuracy artificial intelligent internet of things augmentation blockchain classification and grading client selection Clinical and internal medicine clustering communication efficiency convolutional neural network deep learning differential privacy dingo optimization algorithm disease risk prediction Diseases and disorders dynamic watermarking edge cloud edge cloud computing edge computing federated learning Federated Learning (FL) financial scenarios homomorphic encryption image classification Internet of Things Internet of Vehicles (IoV) intrusion detection systems (IDS) IoT machine learning Medicine and Nursing model aggregation n/a OFD files Oncology privacy privacy-preserving proof-of-concept raspberry PI salp swarm algorithm semantic analysis semi-synchronous sensitive data split federated learning split learning synonym mining transfer learning virtual machines
ISBN:	3725819939, 9783725819935, 3725819947, 9783725819942
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