5 citations · 8 across the 3 of their papers we have counts for
3 papers
On Biased Behavior of GANs for Face Verification
Sasikanth Kotti, Mayank Vatsa, Richa Singh
Deep Learning systems need large data for training. Datasets for training face verification systems are difficult to obtain and prone to privacy issues. Synthetic data generated by…
When Differential Privacy Meets Interpretability: A Case Study
Rakshit Naidu, Aman Priyanshu, Aadith Kumar +3
Given the increase in the use of personal data for training Deep Neural Networks (DNNs) in tasks such as medical imaging and diagnosis, differentially private training of DNNs is s…
DP-SGD vs PATE: Which Has Less Disparate Impact on Model Accuracy?
Archit Uniyal, Rakshit Naidu, Sasikanth Kotti +4
Recent advances in differentially private deep learning have demonstrated that application of differential privacy, specifically the DP-SGD algorithm, has a disparate impact on dif…