28 citations · 57 across the 10 of their papers we have counts for
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cs.LG2019★ 18 cited
DP-LSSGD: A Stochastic Optimization Method to Lift the Utility in Privacy-Preserving ERM
Bao Wang, Quanquan Gu, March Boedihardjo +2
Machine learning (ML) models trained by differentially private stochastic gradient descent (DP-SGD) have much lower utility than the non-private ones. To mitigate this degradation,…
cs.LG2018★ 28 cited
Laplacian Smoothing Gradient Descent
Stanley Osher, Bao Wang, Penghang Yin +4
We propose a class of very simple modifications of gradient descent and stochastic gradient descent. We show that when applied to a large variety of machine learning problems, rang…