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stat.ML2021★ 4 cited
An Analysis of the Deployment of Models Trained on Private Tabular Synthetic Data: Unexpected Surprises
Mayana Pereira, Meghana Kshirsagar, Sumit Mukherjee +2
Diferentially private (DP) synthetic datasets are a powerful approach for training machine learning models while respecting the privacy of individual data providers. The effect of…
stat.ML2021
Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary
Jean-Francois Rajotte, Sumit Mukherjee, Caleb Robinson +4
We introduce FELICIA (FEderated LearnIng with a CentralIzed Adversary) a generative mechanism enabling collaborative learning. In particular, we show how a data owner with limited…