3 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2021★ 3 cited
Public Data-Assisted Mirror Descent for Private Model Training
Ehsan Amid, Arun Ganesh, Rajiv Mathews +6
In this paper, we revisit the problem of using in-distribution public data to improve the privacy/utility trade-offs for differentially private (DP) model training. (Here, public d…
stat.ML2021
The Role of Adaptive Optimizers for Honest Private Hyperparameter Selection
Shubhankar Mohapatra, Sajin Sasy, Xi He +2
Hyperparameter optimization is a ubiquitous challenge in machine learning, and the performance of a trained model depends crucially upon their effective selection. While a rich set…