most citedFLuID: Mitigating Stragglers in Federated Learning using Invariant Dropout

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

collaborators

2 papers

cs.LG2023★ 3 cited

FLuID: Mitigating Stragglers in Federated Learning using Invariant Dropout

Irene Wang, Prashant J. Nair, Divya Mahajan

Federated Learning (FL) allows machine learning models to train locally on individual mobile devices, synchronizing model updates via a shared server. This approach safeguards user…

cs.LG2022

Reducing Impacts of System Heterogeneity in Federated Learning using Weight Update Magnitudes

Irene Wang

The widespread adoption of handheld devices have fueled rapid growth in new applications. Several of these new applications employ machine learning models to train on user data tha…