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dc.contributor.authorWang, Chengchengen_US
dc.contributor.authorTay, Wee Pengen_US
dc.contributor.authorWang, Yuanen_US
dc.contributor.authorWei, Yeen_US
dc.identifier.citationWang, C., Tay, W. P., Wang, Y., & Wei, Y. (2019). A privacy-preserving diffusion strategy over multitask networks. Proceedings of the 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 7600-7604. doi:10.1109/ICASSP.2019.8682425en_US
dc.description.abstractWe develop a privacy-preserving distributed strategy over multitask diffusion networks, where each agent is interested in not only improving its local inference performance via in-network cooperation, but also protecting its own individual task against privacy leakage. In the proposed strategy, at each time instant, each agent sends a noisy estimate, which is its local intermediate estimate corrupted by a zero-mean additive noise, to its neighboring agents. We derive a sufficient condition to determine the amount of noise to add to each agent's intermediate estimate to achieve an optimal trade-off between the steady-state network mean-square-deviation and an inference privacy constraint. We show that the proposed noise powers are bounded and convergent, which leads to mean-square convergence of the proposed privacy-preserving multitask diffusion scheme. Simulation results demonstrate that the proposed strategy is able to balance the trade-off between estimation accuracy and privacy preservation.en_US
dc.description.sponsorshipNRF (Natl Research Foundation, S’pore)en_US
dc.rights© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works. The published version is available at:
dc.subjectEngineering::Electrical and electronic engineeringen_US
dc.titleA privacy-preserving diffusion strategy over multitask networksen_US
dc.typeConference Paperen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.contributor.conference2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)en_US
dc.description.versionAccepted versionen_US
dc.subject.keywordsDistributed Strategiesen_US
dc.subject.keywordsDiffusion Strategiesen_US
dc.citation.conferencelocationBrighton, United Kingdomen_US
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