Learning Resource-Aware Classifiers for Mobile Devices: From Regularization to Energy Efficiency

@article{Oneto2015LearningRC,
  title={Learning Resource-Aware Classifiers for Mobile Devices: From Regularization to Energy Efficiency},
  author={Luca Oneto and Alessandro Ghio and Sandro Ridella and Davide Anguita},
  journal={Neurocomputing},
  year={2015},
  volume={169},
  pages={225-235}
}
Mobile devices are resource-limited systems that provide a large number of services and features. Smartphones, for example, implement advanced functionalities and services for the final user, in addition to conventional communication capabilities. Machine Learning algorithms can help in providing such advanced functionalities, but mobile systems suffer from issues related to their resource-limited nature such as, for example, limited battery capacity and processing power and, therefore, even… CONTINUE READING

References

Publications referenced by this paper.

Similar Papers

Loading similar papers…