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cs.LG2022★ 15 cited
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…
cs.LG2021
PACMAN: PAC-style bounds accounting for the Mismatch between Accuracy and Negative log-loss
Matias Vera, Leonardo Rey Vega, Pablo Piantanida
The ultimate performance of machine learning algorithms for classification tasks is usually measured in terms of the empirical error probability (or accuracy) based on a testing da…