5 citations · 17 across the 8 of their papers we have counts for
3 papers · 1 filter
Adversarial Stacked Auto-Encoders for Fair Representation Learning
Patrik Joslin Kenfack, Adil Mehmood Khan, Rasheed Hussain +1
Training machine learning models with the only accuracy as a final goal may promote prejudices and discriminatory behaviors embedded in the data. One solution is to learn latent re…
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…
On the Fairness of Generative Adversarial Networks (GANs)
Patrik Joslin Kenfack, Daniil Dmitrievich Arapov, Rasheed Hussain +2
Generative adversarial networks (GANs) are one of the greatest advances in AI in recent years. With their ability to directly learn the probability distribution of data, and then s…