Feature Distribution Matching for Federated Domain Generalization
Paper
• 2203.11635 • Published
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Check out the documentation for more information.
FedKA that consists of three building blocks, i.e., features disentangler, embedding matching, and federated voting, aims to improve the global model’s generality in tackling an unseen task with knowledge transferred from different clients’ model learning.
The systems in the Digit-Five tasks can be run with the Jupyter Notebook "FedKA-Digit-Five.ipynb". The dataset can be downloaded from Digit-Five.