10 citations · 14 across the 3 of their papers we have counts for
3 papers
cs.CR2020★ 4 cited
Minimal Model Structure Analysis for Input Reconstruction in Federated Learning
Jia Qian, Hiba Nassar, Lars Kai Hansen
\ac{fl} proposed a distributed \ac{ml} framework where every distributed worker owns a complete copy of global model and their own data. The training is occurred locally, which ass…
cs.DC2020
Robustness analytics to data heterogeneity in edge computing
Jia Qian, Lars Kai Hansen, Xenofon Fafoutis +2
Federated Learning is a framework that jointly trains a model \textit{with} complete knowledge on a remotely placed centralized server, but \textit{without} the requirement of acce…
cs.DC2019★ 10 cited
Active Learning Solution on Distributed Edge Computing
Jia Qian, Sayantan Sengupta, Lars Kai Hansen
Industry 4.0 becomes possible through the convergence between Operational and Information Technologies. All the requirements to realize the convergence is integrated on the Fog Pla…