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Partitioned Hierarchical Alternating Least Squares Algorithm for CP Tensor Decomposition

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00472586" target="_blank" >RIV/67985556:_____/17:00472586 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.13140/RG.2.2.29610.82882" target="_blank" >http://dx.doi.org/10.13140/RG.2.2.29610.82882</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.13140/RG.2.2.29610.82882" target="_blank" >10.13140/RG.2.2.29610.82882</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Partitioned Hierarchical Alternating Least Squares Algorithm for CP Tensor Decomposition

  • Original language description

    Canonical polyadic decomposition (CPD), also known as PARAFAC, is a representation of a given tensor as a sum of rank-one tensors. Traditional method for accomplishing CPD is the alternating least squares (ALS) algorithm. This algorithm is easy to implement with very low computationalncomplexity per iteration. A disadvantage is that in difficult scenarios, where factor matrices in the decomposition contain nearly collinear columns, the number of iterations needed to achieve convergence might be very large. In this paper, we propose a modification of the algorithm which has similar complexity per iteration as ALS, but in difficult scenarios it needs a significantly lower number of iterations.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10103 - Statistics and probability

Result continuities

  • Project

    <a href="/en/project/GA17-00902S" target="_blank" >GA17-00902S: Advanded Joint Blind Source Separation Methods</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2017

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    2017 IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2017

  • ISBN

    978-1-5090-4116-9

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    2542-2546

  • Publisher name

    IEEE

  • Place of publication

    New Orleans

  • Event location

    New Orleans

  • Event date

    Mar 5, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000414286202143