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This is a PyTorch implementation of the paper Multi-Source Domain Adaptation Based on Federated Knowledge Alignment.

Table of Contents

General 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.

Running the systems

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.

Further readings

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