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http://hdl.handle.net/1942/23987
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DC Field | Value | Language |
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dc.contributor.author | Vander Aa, Tom | - |
dc.contributor.author | Chakroun, Imen | - |
dc.contributor.author | HABER, Tom | - |
dc.date.accessioned | 2017-07-17T09:12:15Z | - |
dc.date.available | 2017-07-17T09:12:15Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | 2016 IEEE International Conference on Cluster Computing (CLUSTER), IEEE,p. 346-349 | - |
dc.identifier.isbn | 9781509036530 | - |
dc.identifier.issn | 1552-5244 | - |
dc.identifier.uri | http://hdl.handle.net/1942/23987 | - |
dc.description.abstract | Matrix factorization is a common machine learning technique for recommender systems. Despite its high prediction accuracy, the Bayesian Probabilistic Matrix Factorization algorithm (BPMF) has not been widely used on large scale data because of its high computational cost. In this paper we propose a distributed high-performance parallel implementation of BPMF on shared memory and distributed architectures. We show by using efficient load balancing using work stealing on a single node, and by using asynchronous communication in the distributed version we beat state of the art implementations. | - |
dc.description.sponsorship | This work is partly funded by the European projects EXA2CT (EXascale Algorithms and Advanced Computational Techniques) and ExCAPE (Exascale Compound Activity Prediction Engine) with references 610741 and 671555. We acknowledge PRACE for awarding us access to resource Fermi based in Italy at CINECA and IT4I for providing access to the Anselm and Salamon systems. | - |
dc.language.iso | en | - |
dc.publisher | IEEE | - |
dc.relation.ispartofseries | IEEE International Conference on Cluster Computing | - |
dc.rights | © 2016 IEEE | - |
dc.subject.other | probabilistic matrix factorization; collaborative filtering; machine learning; distributed systems; multi-core | - |
dc.title | Distributed Bayesian Probabilistic Matrix Factorization | - |
dc.type | Proceedings Paper | - |
local.bibliographicCitation.conferencedate | 13-15/09/2016 | - |
local.bibliographicCitation.conferencename | IEEE International Conference on Cluster Computing (CLUSTER) | - |
local.bibliographicCitation.conferenceplace | Taipei, Taiwan | - |
dc.identifier.epage | 349 | - |
dc.identifier.spage | 346 | - |
local.bibliographicCitation.jcat | C1 | - |
local.publisher.place | New York, NY, USA | - |
local.type.refereed | Refereed | - |
local.type.specified | Proceedings Paper | - |
dc.identifier.doi | 10.1109/CLUSTER.2016.13 | - |
dc.identifier.isi | 000391414100056 | - |
local.bibliographicCitation.btitle | 2016 IEEE International Conference on Cluster Computing (CLUSTER) | - |
item.accessRights | Restricted Access | - |
item.contributor | Vander Aa, Tom | - |
item.contributor | Chakroun, Imen | - |
item.contributor | HABER, Tom | - |
item.fulltext | With Fulltext | - |
item.fullcitation | Vander Aa, Tom; Chakroun, Imen & HABER, Tom (2016) Distributed Bayesian Probabilistic Matrix Factorization. In: 2016 IEEE International Conference on Cluster Computing (CLUSTER), IEEE,p. 346-349. | - |
item.validation | ecoom 2018 | - |
Appears in Collections: | Research publications |
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aa2016.pdf Restricted Access | Published version | 600.46 kB | Adobe PDF | View/Open Request a copy |
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