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Federated Learning for Short-term Residential Load Forecasting
Load forecasting is an essential task performed within the energy industry to help balance supply with demand and maintain a stable load on the electricity grid.
Privacy Preserving Demand Forecasting to Encourage Consumer Acceptance of Smart Energy Meters
In this proposal paper we highlight the need for privacy preserving energy demand forecasting to allay a major concern consumers have about smart meter installations.
Federated learning with hierarchical clustering of local updates to improve training on non-IID data
However in settings where data is distributed in a non-iid (not independent and identically distributed) fashion -- as is typical in real world situations -- the joint model produced by FL suffers in terms of test set accuracy and/or communication costs compared to training on iid data.
A Review of Privacy-preserving Federated Learning for the Internet-of-Things
The Internet-of-Things (IoT) generates vast quantities of data, much of it attributable to individuals' activity and behaviour.
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