338 citations · 448 across the 13 of their papers we have counts for
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cs.DC2021
BESS Aided Reconfigurable Energy Supply using Deep Reinforcement Learning for 5G and Beyond
Hao Yuan, Guoming Tang, Deke Guo +4
The year of 2020 has witnessed the unprecedented development of 5G networks, along with the widespread deployment of 5G base stations (BSs). Nevertheless, the enormous energy consu…
cs.LG2021★ 6 cited
FedNILM: Applying Federated Learning to NILM Applications at the Edge
Yu Zhang, Guoming Tang, Qianyi Huang +3
Non-intrusive load monitoring (NILM) helps disaggregate the household's main electricity consumption to energy usages of individual appliances, thus greatly cutting down the cost i…
cs.LG2021
More Behind Your Electricity Bill: a Dual-DNN Approach to Non-Intrusive Load Monitoring
Yu Zhang, Guoming Tang, Qianyi Huang +2
Non-intrusive load monitoring (NILM) is a well-known single-channel blind source separation problem that aims to decompose the household energy consumption into itemised energy usa…