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cs.LG2024
On the Conflict of Robustness and Learning in Collaborative Machine Learning
Mathilde Raynal, Carmela Troncoso
Collaborative Machine Learning (CML) allows participants to jointly train a machine learning model while keeping their training data private. In many scenarios where CML is seen as…
cs.LG2023★ 5 cited
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…