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Alternating optimization for tensor factorization with orthogonality constraints: Algorithm and parallel implementation

Karakasis Paris, Liavas Athanasios

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URIhttp://purl.tuc.gr/dl/dias/9FBFF227-DC43-4975-95E9-2589F7F407A4-
Identifierhttps://doi.org/10.1109/HPCS.2018.00076-
Identifierhttps://ieeexplore.ieee.org/document/8514381-
Languageen-
Extent6 pagesen
TitleAlternating optimization for tensor factorization with orthogonality constraints: Algorithm and parallel implementationen
CreatorKarakasis Parisen
CreatorΚαρακασης Παριςel
CreatorLiavas Athanasiosen
CreatorΛιαβας Αθανασιοςel
PublisherInstitute of Electrical and Electronics Engineersen
Content SummaryWe consider the problem of tensor factorization in the cases where one of the factors is constrained to have orthonormal columns. We adopt the alternating optimization framework and derive an efficient algorithm that is also suitable for parallel implementation. We describe in detail a distributed memory implementation of the algorithm on a three-dimensional processor grid. The speedup attained by a message-passing implementation of the algorithm is significant, indicating that it is a competitive candidate for the solution of very large tensor factorization problems with orthogonality constraints.en
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2019-05-31-
Date of Publication2018-
SubjectAlgorithmsen
SubjectOrthogonality constraintsen
SubjectPARAFACen
SubjectParallel algorithmsen
SubjectTensor factorizationen
SubjectTensorsen
Bibliographic CitationP. A. Karakasis and A. P. Liavas, "Alternating optimization for tensor factorization with orthogonality constraints: algorithm and parallel implementation," in 16th International Conference on High Performance Computing and Simulation, 2018, pp. 439-444. doi: 10.1109/HPCS.2018.00076en

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