12 citations · 12 across the 8 of their papers we have counts for
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cs.LG2024
Tackling Data Heterogeneity in Federated Time Series Forecasting
Wei Yuan, Guanhua Ye, Xiangyu Zhao +3
Time series forecasting plays a critical role in various real-world applications, including energy consumption prediction, disease transmission monitoring, and weather forecasting.…
cs.LG2024
Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning
Saber Malekmohammadi, Yaoliang Yu, Yang Cao
High utility and rigorous data privacy are of the main goals of a federated learning (FL) system, which learns a model from the data distributed among some clients. The latter has…
cs.CR2024★ 12 cited
Differentially Private Federated Learning: A Systematic Review
Jie Fu, Yuan Hong, Xinpeng Ling +6
In recent years, privacy and security concerns in machine learning have promoted trusted federated learning to the forefront of research. Differential privacy has emerged as the de…