Federated learning (FL) emerges as a popular distributed learning schema that learns a model from a set of participating users without requiring raw data to be shared. One major challenge of FL comes from heterogeneity in users, which may have …
Recently, self-supervised contrastive pre-training has become the de facto regime, that allows for efficient downstream fine-tuning. Meanwhile, its fairness issues are barely studied, though they have drawn great attention from the machine learning …
Deep neural networks (DNNs) are vulnerable to backdoor attacks. Previous works have shown it extremely challenging to unlearn the undesired backdoor behavior from the network, since the entire network can be affected by the backdoor samples. In this …