Our paper Disparate Impact on Group Accuracy of Linearization for Private Inference was accepted to appear at the Forty-first International Conference on Machine Learning (ICML 2024)! In this paper we analyzed the effects on Fairness due to ReLU budgeting for Private Inference speedup.
A huge shout-out to my great colleagues Saswat and Ferdinando for their amazing work!
Marco Romanelli
Research Associate
My research interests include applications of Information Theory notions to Privacy and Security, Safety in AI, Machine Learning and Information Leakage Measurement.