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Federated Learning of Shareable Bases for Personalization-Friendly Image Classification
FedBasis learns a set of few shareable ``basis'' models, which can be linearly combined to form personalized models for clients.
Making Batch Normalization Great in Federated Deep Learning
We reinvestigate factors that are believed to cause this problem, including the mismatch of BN statistics across clients and the deviation of gradients during local training.
Learning with Free Object Segments for Long-Tailed Instance Segmentation
One fundamental challenge in building an instance segmentation model for a large number of classes in complex scenes is the lack of training examples, especially for rare objects.
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