34 citations · 83 across the 11 of their papers we have counts for
3 papers · 1 filter
Leveraging Adversarial Examples to Quantify Membership Information Leakage
Ganesh Del Grosso, Hamid Jalalzai, Georg Pichler +2
The use of personal data for training machine learning systems comes with a privacy threat and measuring the level of privacy of a model is one of the major challenges in machine l…
Perfectly Accurate Membership Inference by a Dishonest Central Server in Federated Learning
Georg Pichler, Marco Romanelli, Leonardo Rey Vega +1
Federated Learning is expected to provide strong privacy guarantees, as only gradients or model parameters but no plain text training data is ever exchanged either between the clie…
A Differential Entropy Estimator for Training Neural Networks
Georg Pichler, Pierre Colombo, Malik Boudiaf +2
Mutual Information (MI) has been widely used as a loss regularizer for training neural networks. This has been particularly effective when learn disentangled or compressed represen…