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20172022
most citedA Fair and Efficient Hybrid Federated Learning Framework based on XGBoost for Distributed Power Prediction

10 citations · 16 across the 7 of their papers we have counts for

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cs.LG2022★ 10 cited

A Fair and Efficient Hybrid Federated Learning Framework based on XGBoost for Distributed Power Prediction

Haizhou Liu, Xuan Zhang, Xinwei Shen +1

In a modern power system, real-time data on power generation/consumption and its relevant features are stored in various distributed parties, including household meters, transforme…

cs.LG2021

A Federated Learning Framework for Smart Grids: Securing Power Traces in Collaborative Learning

Haizhou Liu, Xuan Zhang, Xinwei Shen +1

With the deployment of smart sensors and advancements in communication technologies, big data analytics have become vastly popular in the smart grid domain, informing stakeholders…