5 citations · 12 across the 5 of their papers we have counts for
7 papers
CaPS: Collaborative and Private Synthetic Data Generation from Distributed Sources
Sikha Pentyala, Mayana Pereira, Martine De Cock
Data is the lifeblood of the modern world, forming a fundamental part of AI, decision-making, and research advances. With increase in interest in data, governments have taken impor…
Assessment of Differentially Private Synthetic Data for Utility and Fairness in End-to-End Machine Learning Pipelines for Tabular Data
Mayana Pereira, Meghana Kshirsagar, Sumit Mukherjee +3
Differentially private (DP) synthetic data sets are a solution for sharing data while preserving the privacy of individual data providers. Understanding the effects of utilizing DP…
Navigating the Web of Misinformation: A Framework for Misinformation Domain Detection Using Browser Traffic
Mayana Pereira, Kevin Greene, Nilima Pisharody +3
The proliferation of misinformation and propaganda is a global challenge, with profound effects during major crises such as the COVID-19 pandemic and the Russian invasion of Ukrain…
Secure Multiparty Computation for Synthetic Data Generation from Distributed Data
Mayana Pereira, Sikha Pentyala, Anderson Nascimento +2
Legal and ethical restrictions on accessing relevant data inhibit data science research in critical domains such as health, finance, and education. Synthetic data generation algori…
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…
U.S. Broadband Coverage Data Set: A Differentially Private Data Release
Mayana Pereira, Allen Kim, Joshua Allen +3
Broadband connectivity is a key metric in today's economy. In an era of rapid expansion of the digital economy, it directly impacts GDP. Furthermore, with the COVID-19 guidelines o…