Results 231 to 234 of about 91,570 (234)

Federated Learning

2023
Federated Learning for bone ...
Yaochu Jin, Hangyu Zhu, Jinjin Xu, Yang Chen   +3 more
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Federated Learning

Journal of Artificial Intelligence & Cloud Computing, 2022
Federated Learning (FL) serves as one of the groundbreaking approaches in the present society, particularly in smart mobile applications, for designing a distributed environment for clients' model training without compromising data ownership. This paper narrows down the focus to how FL emerged, how it fits in distributed systems, and its usefulness in ...
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Federated Learning

IEEE Consumer Electronics Magazine, 2021
Now we are in an era of technology transformation in our everyday life, where data play a key role in the decision making and bringing the action into reality. These data are collected from many distributed sources. Another important concept in this process is machine learning (ML) and data analytics.
Niranjan K. Ray, Deepak Puthal, Dhruva Ghai   +2 more
openaire   +1 more source

Utility-preserving Federated Learning

Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security, 2023
We investigate the concept of utility-preserving federated learning (UPFL) in the context of deep neural networks. We theoretically prove and experimentally validate that UPFL achieves the same accuracy as centralized training independent of the data distribution across the clients.
Reza Nasirigerdeh, Daniel Rueckert, Georgios Kaissis   +2 more
openaire   +2 more sources