Evaluating data distribution strategies in federated learning: A trade-off analysis between privacy and performance for IoT security
(2023)
Conference Proceeding
White, J., & Legg, P. (in press). Evaluating data distribution strategies in federated learning: A trade-off analysis between privacy and performance for IoT security.
Federated learning is an effective approach for training a global machine learning model. It uses locally acquired data without having to share local data with the centralised server. This method provides a machine learning model beneficial for all p... Read More about Evaluating data distribution strategies in federated learning: A trade-off analysis between privacy and performance for IoT security.