Crowd-ML: A Privacy-Preserving Learning Framework for a Crowd of Smart Devices

Abstract

Smart devices with built-in sensors, computational capabilities, and network connectivity have become increasingly pervasive. Crowds of smart devices offer opportunities to collectively sense and perform computing tasks at an unprecedented scale. This paper presents Crowd-ML, a privacy-preserving machine learning framework for a crowd of smart devices… (More)
DOI: 10.1109/ICDCS.2015.10

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Cite this paper

@article{Hamm2015CrowdMLAP, title={Crowd-ML: A Privacy-Preserving Learning Framework for a Crowd of Smart Devices}, author={Jihun Hamm and Adam C. Champion and Guoxing Chen and Mikhail Belkin and Dong Xuan}, journal={2015 IEEE 35th International Conference on Distributed Computing Systems}, year={2015}, pages={11-20} }