1 code implementation • 31 Jan 2024 • Konstantin Donhauser, Javier Abad, Neha Hulkund, Fanny Yang
We present a novel approach for differentially private data synthesis of protected tabular datasets, a relevant task in highly sensitive domains such as healthcare and government.
no code implementations • 4 Aug 2022 • Neha Hulkund, Nicolo Fusi, Jennifer Wortman Vaughan, David Alvarez-Melis
We propose a method to identify and characterize distribution shifts in classification datasets based on optimal transport.
no code implementations • 5 Jul 2022 • Nathan Ng, Neha Hulkund, Kyunghyun Cho, Marzyeh Ghassemi
Developing and deploying machine learning models safely depends on the ability to characterize and compare their abilities to generalize to new environments.
no code implementations • 7 Jul 2021 • Shobhita Sundaram, Neha Hulkund
A common problem in computer vision -- particularly in medical applications -- is a lack of sufficiently diverse, large sets of training data.