Leveraging graphical models to improve accuracy and reduce privacy risks of mobile sensing

@inproceedings{Parate2013LeveragingGM,
  title={Leveraging graphical models to improve accuracy and reduce privacy risks of mobile sensing},
  author={Abhinav Parate and Meng-Chieh Chiu and Deepak Ganesan and Benjamin M. Marlin},
  booktitle={MobiSys},
  year={2013}
}
The proliferation of sensors on mobile phones and wearables has led to a plethora of context classifiers designed to sense the individual's context. We argue that a key missing piece in mobile inference is a layer that fuses the outputs of several classifiers to learn deeper insights into an individual's habitual patterns and associated correlations between contexts, thereby enabling new systems optimizations and opportunities. In this paper, we design CQue, a dynamic bayesian network that… CONTINUE READING
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