167 citations · 194 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 7 cited
On the Convergence of Federated Averaging with Cyclic Client Participation
Yae Jee Cho, Pranay Sharma, Gauri Joshi +3
Federated Averaging (FedAvg) and its variants are the most popular optimization algorithms in federated learning (FL). Previous convergence analyses of FedAvg either assume full cl…
cs.LG2022★ 20 cited
On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data
Jianyu Wang, Rudrajit Das, Gauri Joshi +3
Existing theory predicts that data heterogeneity will degrade the performance of the Federated Averaging (FedAvg) algorithm in federated learning. However, in practice, the simple…
cs.LG2021★ 167 cited
A Field Guide to Federated Optimization
Jianyu Wang, Zachary Charles, Zheng Xu +50
Federated learning and analytics are a distributed approach for collaboratively learning models (or statistics) from decentralized data, motivated by and designed for privacy prote…