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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.LG2022★ 1 cited
Beyond Uniform Lipschitz Condition in Differentially Private Optimization
Rudrajit Das, Satyen Kale, Zheng Xu +2
Most prior results on differentially private stochastic gradient descent (DP-SGD) are derived under the simplistic assumption of uniform Lipschitzness, i.e., the per-sample gradien…