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hello everyone i am xiaomi oh young this is a joint work with students professor jai jo professor jim hwang and my supervisor professor guoliangshin human activity recognition has lots of applications such as finish tracking sleep monitoring and social distancing recently many machine learning algorithms have been applied to humanities recognition however current approach is most based on centralized learning that require users to send raw data which imposes docHub privacy concerns so how about store the data locally federated learning is a new machine learning paradigm it enables collaborative training models while keeping the data residing on devices however the single global model is not accurate for all users as shown by several recent papers moreover transmitting motorways back and forth will cause docHub communication overhead our key insight is that there exhibits intrinsic similarities among users activity data due to human biological features physical environments or
