2 citations · 2 across the 2 of their papers we have counts for
3 papers
Decouple-and-Sample: Protecting sensitive information in task agnostic data release
Abhishek Singh, Ethan Garza, Ayush Chopra +3
We propose sanitizer, a framework for secure and task-agnostic data release. While releasing datasets continues to make a big impact in various applications of computer vision, its…
Private measurement of nonlinear correlations between data hosted across multiple parties
Praneeth Vepakomma, Subha Nawer Pushpita, Ramesh Raskar
We introduce a differentially private method to measure nonlinear correlations between sensitive data hosted across two entities. We provide utility guarantees of our private estim…
PrivateMail: Supervised Manifold Learning of Deep Features With Differential Privacy for Image Retrieval
Praneeth Vepakomma, Julia Balla, Ramesh Raskar
Differential Privacy offers strong guarantees such as immutable privacy under post processing. Thus it is often looked to as a solution to learning on scattered and isolated data.…