9 citations · 17 across the 11 of their papers we have counts for
3 papers · 1 filter
Can Decentralized Learning be more robust than Federated Learning?
Mathilde Raynal, Dario Pasquini, Carmela Troncoso
Decentralized Learning (DL) is a peer--to--peer learning approach that allows a group of users to jointly train a machine learning model. To ensure correctness, DL should be robust…
Eluding Secure Aggregation in Federated Learning via Model Inconsistency
Dario Pasquini, Danilo Francati, Giuseppe Ateniese
Secure aggregation is a cryptographic protocol that securely computes the aggregation of its inputs. It is pivotal in keeping model updates private in federated learning. Indeed, t…
Adversarial Out-domain Examples for Generative Models
Dario Pasquini, Marco Mingione, Massimo Bernaschi
Deep generative models are rapidly becoming a common tool for researchers and developers. However, as exhaustively shown for the family of discriminative models, the test-time infe…