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Heterogeneous federated learning: State-of-the-art and research challenges
Federated learning (FL) has drawn increasing attention owing to its potential use in large-
scale industrial applications. Existing FL works mainly focus on model homogeneous …
scale industrial applications. Existing FL works mainly focus on model homogeneous …
Federated learning review: Fundamentals, enabling technologies, and future applications
Federated Learning (FL) has been foundational in improving the performance of a wide
range of applications since it was first introduced by Google. Some of the most prominent …
range of applications since it was first introduced by Google. Some of the most prominent …
A review of applications in federated learning
L Li, Y Fan, M Tse, KY Lin - Computers & Industrial Engineering, 2020 - Elsevier
Federated Learning (FL) is a collaboratively decentralized privacy-preserving technology to
overcome challenges of data silos and data sensibility. Exactly what research is carrying the …
overcome challenges of data silos and data sensibility. Exactly what research is carrying the …
Federated learning in smart cities: Privacy and security survey
Over the last decade, smart cities (SC) have been developed worldwide. Implementing big
data and the internet of things improves the monitoring and integration of different …
data and the internet of things improves the monitoring and integration of different …
Clusterfl: a similarity-aware federated learning system for human activity recognition
X Ouyang, Z ** review
Background Artificial intelligence (AI) has revolutionized health care delivery in recent years.
There is an increase in research for advanced AI techniques, such as deep learning, to build …
There is an increase in research for advanced AI techniques, such as deep learning, to build …