most citedSample-based and Feature-based Federated Learning for Unconstrained and Constrained Nonconvex Optimization via Mini-batch SSCA

9 citations · 10 across the 2 of their papers we have counts for

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2 papers

cs.LG2021★ 9 cited

Sample-based and Feature-based Federated Learning for Unconstrained and Constrained Nonconvex Optimization via Mini-batch SSCA

Ying Cui, Yangchen Li, Chencheng Ye

Federated learning (FL) has become a hot research area in enabling the collaborative training of machine learning models among multiple clients that hold sensitive local data. Neve…

cs.LG2021★ 1 cited

Sample-based Federated Learning via Mini-batch SSCA

Chencheng Ye, Ying Cui

In this paper, we investigate unconstrained and constrained sample-based federated optimization, respectively. For each problem, we propose a privacy preserving algorithm using sto…