100 citations · 152 across the 9 of their papers we have counts for
4 papers · 1 filter
Bridging the Gap: Rademacher Complexity in Robust and Standard Generalization
Jiancong Xiao, Ruoyu Sun, Qi Long +1
Training Deep Neural Networks (DNNs) with adversarial examples often results in poor generalization to test-time adversarial data. This paper investigates this issue, known as adve…
Unified Enhancement of Privacy Bounds for Mixture Mechanisms via -Differential Privacy
Chendi Wang, Buxin Su, Jiayuan Ye +2
Differentially private (DP) machine learning algorithms incur many sources of randomness, such as random initialization, random batch subsampling, and shuffling. However, such rand…
The Implicit Regularization of Dynamical Stability in Stochastic Gradient Descent
Lei Wu, Weijie J. Su
In this paper, we study the implicit regularization of stochastic gradient descent (SGD) through the lens of {\em dynamical stability} (Wu et al., 2018). We start by revising exist…
The alignment property of SGD noise and how it helps select flat minima: A stability analysis
Lei Wu, Mingze Wang, Weijie Su
The phenomenon that stochastic gradient descent (SGD) favors flat minima has played a critical role in understanding the implicit regularization of SGD. In this paper, we provide a…