WebFLSys is designed to work with mobile sensing data collected on smart phones, balance model performance with resource consumption on the phones, tolerate phone communication failures, and achieve scalability in the cloud. Data Augmentation Federated Learning +2 Paper Add Code WebFurthermore, FLSys provides advanced privacy preserving mechanisms and a common API for third-party app developers to access FL models. FLSys adopts a modular design and is implemented in Android and AWS cloud. We co-designed FLSys with a human activity recognition (HAR) model.
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