3 papers
cs.LG2023
Data Minimization at Inference Time
Cuong Tran, Ferdinando Fioretto
In domains with high stakes such as law, recruitment, and healthcare, learning models frequently rely on sensitive user data for inference, necessitating the complete set of featur…
cs.LG2023
On the Fairness Impacts of Private Ensembles Models
Cuong Tran, Ferdinando Fioretto
The Private Aggregation of Teacher Ensembles (PATE) is a machine learning framework that enables the creation of private models through the combination of multiple "teacher" models…
cs.LG2023
Personalized Privacy Auditing and Optimization at Test Time
Cuong Tran, Ferdinando Fioretto
A number of learning models used in consequential domains, such as to assist in legal, banking, hiring, and healthcare decisions, make use of potentially sensitive users' informati…