Corpus ID: 214714053

Streamlined Empirical Bayes Fitting of Linear Mixed Models in Mobile Health

@article{Menictas2020StreamlinedEB,
  title={Streamlined Empirical Bayes Fitting of Linear Mixed Models in Mobile Health},
  author={M. Menictas and S. Tomkins and S. A. Murphy},
  journal={ArXiv},
  year={2020},
  volume={abs/2003.12881}
}

M. Menictas, S. Tomkins, S. A. Murphy

Published 2020

Computer Science, Mathematics

ArXiv

To effect behavior change a successful algorithm must make high-quality decisions in real-time. For example, a mobile health (mHealth) application designed to increase physical activity must make contextually relevant suggestions to motivate users. While machine learning offers solutions for certain stylized settings, such as when batch data can be processed offline, there is a dearth of approaches which can deliver high-quality solutions under the specific constraints of mHealth. We propose an… CONTINUE READING

View PDF on arXiv

Save to Library

Create Alert

Cite

Launch Research Feed