most citedDearFSAC: An Approach to Optimizing Unreliable Federated Learning via Deep Reinforcement Learning

3 citations · 4 across the 2 of their papers we have counts for

collaborators

2 papers

cs.DC2022★ 1 cited

Deep Reinforcement Learning-Assisted Federated Learning for Robust Short-term Utility Demand Forecasting in Electricity Wholesale Markets

Chenghao Huang, Weilong Chen, Shengrong Bu +1

Short-term load forecasting (STLF) plays a significant role in the operation of electricity trading markets. Considering the growing concern of data privacy, federated learning (FL…

cs.LG2022★ 3 cited

DearFSAC: An Approach to Optimizing Unreliable Federated Learning via Deep Reinforcement Learning

Chenghao Huang, Weilong Chen, Yuxi Chen +2

In federated learning (FL), model aggregation has been widely adopted for data privacy. In recent years, assigning different weights to local models has been used to alleviate the…