9 citations · 12 across the 6 of their papers we have counts for
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cs.LG2025★ 2 cited
Towards Reliable and Generalizable Differentially Private Machine Learning (Extended Version)
Wenxuan Bao, Vincent Bindschaedler
There is a flurry of recent research papers proposing novel differentially private machine learning (DPML) techniques. These papers claim to achieve new state-of-the-art (SoTA) res…
cs.LG2023★ 1 cited
DP-Mix: Mixup-based Data Augmentation for Differentially Private Learning
Wenxuan Bao, Francesco Pittaluga, Vijay Kumar B G +1
Data augmentation techniques, such as simple image transformations and combinations, are highly effective at improving the generalization of computer vision models, especially when…