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Enhancing Privacy against Inversion Attacks in Federated Learning by using Mixing Gradients Strategies
We show that otherwise it is possible to directly recover all vectors in a mini-batch without any numerical optimisation due to the de-mixing nature of the cross entropy loss.
ST-FL: Style Transfer Preprocessing in Federated Learning for COVID-19 Segmentation
We demonstrate that the widely varying data quality on FL client nodes leads to a sub-optimal centralised FL model for COVID-19 chest CT image segmentation.
Senatus -- A Fast and Accurate Code-to-Code Recommendation Engine
Senatus also outperforms standard MinHash LSH by 29. 2\% F1 and 51. 02\emph{x} faster query time.
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