PANORAMIA: Privacy Auditing of Machine Learning Models without Retraining Mishaal Kazmi University of British Columbia Hadrien Lautraite University du Québec à Montréal Alireza Akbari

Nov-19-2025, 10:18:27 GMT–Neural Information Processing Systems 

To circumvent these concerns, Steinke et al. (2023) proposed an auditing recipe (called O(1)) requiring only one training run (which could be the same as the actual training) by randomly including/excluding