most citedFederated learning with hierarchical clustering of local updates to improve training on non-IID data

5 citations · 9 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2021★ 4 cited

Data-driven battery operation for energy arbitrage using rainbow deep reinforcement learning

Daniel J. B. Harrold, Jun Cao, Zhong Fan

As the world seeks to become more sustainable, intelligent solutions are needed to increase the penetration of renewable energy. In this paper, the model-free deep reinforcement le…

cs.LG2020★ 5 cited

Federated learning with hierarchical clustering of local updates to improve training on non-IID data

Christopher Briggs, Zhong Fan, Peter Andras

Federated learning (FL) is a well established method for performing machine learning tasks over massively distributed data. However in settings where data is distributed in a non-i…