RobustSPAM for Inference from Noisy Longitudinal Data and Preservation of Privacy

Palczewska, A, Palczewski, J orcid.org/0000-0003-0235-8746, Aivaliotis, G et al. (1 more author) (2017) RobustSPAM for Inference from Noisy Longitudinal Data and Preservation of Privacy. In: IEEE ICMLA 2017 Conference proceedings. IEEE 16TH International Conference on Machine Learning and Applications - ICMLA 2017, 18-21 Dec 2017, Cancun, Mexico. Institute of Electrical and Electronics Engineers , pp. 344-351. ISBN 978-1-5386-1417-4

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Copyright, Publisher and Additional Information: © 2017 IEEE. This is an author produced version of a paper published in IEEE ICMLA 2017 Conference Proceedings. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Uploaded in accordance with the publisher’s self-archiving policy.
Keywords: robust, temporal pattern, noisy data, privacy
Dates:
  • Published: December 2017
  • Accepted: 21 September 2017
  • Published (online): 18 January 2018
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Maths and Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 06 Oct 2017 08:53
Last Modified: 27 Mar 2018 10:39
Status: Published
Publisher: Institute of Electrical and Electronics Engineers
Identification Number: https://doi.org/10.1109/ICMLA.2017.0-137

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