11 citations · 21 across the 15 of their papers we have counts for
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cs.LG2022
Differentially Private Deep Learning with ModelMix
Hanshen Xiao, Jun Wan, Srinivas Devadas
Training large neural networks with meaningful/usable differential privacy security guarantees is a demanding challenge. In this paper, we tackle this problem by revisiting the two…
cs.LG2021★ 5 cited
High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data
Lijie Hu, Shuo Ni, Hanshen Xiao +1
As one of the most fundamental problems in machine learning, statistics and differential privacy, Differentially Private Stochastic Convex Optimization (DP-SCO) has been extensivel…
cs.LG2020★ 11 cited
On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data
Di Wang, Hanshen Xiao, Srini Devadas +1
In this paper, we consider the problem of designing Differentially Private (DP) algorithms for Stochastic Convex Optimization (SCO) on heavy-tailed data. The irregularity of such d…