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dc.contributor.authorZhao, Jianxin
dc.contributor.authorMortier, Richard
dc.contributor.authorCrowcroft, Jonathon
dc.contributor.authorWang, Liang
dc.date.accessioned2018-09-05T12:51:24Z
dc.date.available2018-09-05T12:51:24Z
dc.date.issued2017
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/279647
dc.description.abstractMachine Learning (ML) techniques, such as Neural Network, are widely used in today's applications. However, there is still a big gap between the current ML systems and users' requirements. ML systems focus on improving the performance of models in training, while individual users cares more about response time and expressiveness of the tool. Many existing research and product begin to move computation towards edge devices. Based on the numerical computing system Owl, we propose to build the Zoo system to support construction, compose, and deployment of ML models on edge and local devices.
dc.subjectcs.LG
dc.subjectcs.LG
dc.subjectcs.CY
dc.titleUser-centric Composable Services: A New Generation of Personal Data Analytics
dc.typeArticle
prism.publicationNameCoRR
dc.identifier.doi10.17863/CAM.27015
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
dc.contributor.orcidMortier, Richard [0000-0001-5205-5992]
dc.contributor.orcidCrowcroft, Jonathon [0000-0002-7013-0121]
rioxxterms.typeJournal Article/Review
pubs.funder-project-idEPSRC (via University of Warwick) (RESWM34910001 CONTRIVE)
pubs.funder-project-idEPSRC (via Queen Mary University of London (QMUL)) (ECSA1W3R)
rioxxterms.freetoread.startdate2019-08-21


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