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Knowing when we do not know: Bayesian continual learning for sensing-based analysis tasks
Our experiments prove the robustness and reliability of the learned models to adapt to the changing sensing environment, and show the suitability of using uncertainty of the predictions to assess their reliability.
Privacy-Preserving Personal Model Training
Many current Internet services rely on inferences from models trained on user data.
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