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Found 3 papers, 1 papers with code
On the Conflict of Robustness and Learning in Collaborative Machine Learning
Collaborative Machine Learning (CML) allows participants to jointly train a machine learning model while keeping their training data private.
Can Decentralized Learning be more robust than Federated Learning?
Decentralized Learning (DL) is a peer--to--peer learning approach that allows a group of users to jointly train a machine learning model.
On the (In)security of Peer-to-Peer Decentralized Machine Learning
In this work, we carry out the first, in-depth, privacy analysis of Decentralized Learning -- a collaborative machine learning framework aimed at addressing the main limitations of federated learning.
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