9 citations · 21 across the 25 of their papers we have counts for
6 papers · 1 filter
Signal Detection in Degree Corrected ERGMs
Yuanzhe Xu, Sumit Mukherjee
In this paper, we study sparse signal detection problems in Degree Corrected Exponential Random Graph Models (ERGMs). We study the performance of two tests based on the conditional…
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…
A machine learning pipeline for aiding school identification from child trafficking images
Sumit Mukherjee, Tina Sederholm, Anthony C. Roman +3
Child trafficking in a serious problem around the world. Every year there are more than 4 million victims of child trafficking around the world, many of them for the purposes of ch…
Becoming Good at AI for Good
Meghana Kshirsagar, Caleb Robinson, Siyu Yang +13
AI for good (AI4G) projects involve developing and applying artificial intelligence (AI) based solutions to further goals in areas such as sustainability, health, humanitarian aid,…
Variational Inference in high-dimensional linear regression
Sumit Mukherjee, Subhabrata Sen
We study high-dimensional Bayesian linear regression with product priors. Using the nascent theory of non-linear large deviations (Chatterjee and Dembo,2016), we derive sufficient…
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…