We simulated different data distribution scenarios and then implemented FedAvg algorithm from scratch. We used entropy and VR as indicators of uncertainty, and ECE score to measure calibration. Then we explored the affect of different model parameters in FL architecture on accuracy, uncertainty and calibration quality.
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Implemented the FedAvg Algorithm in Federated Learning. Completed its uncertainty estimation and confidence calibration.
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