All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Rank-one tensor injection: A novel method for canonical polyadic tensor decomposition

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F16%3A00458487" target="_blank" >RIV/67985556:_____/16:00458487 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Rank-one tensor injection: A novel method for canonical polyadic tensor decomposition

  • Original language description

    Canonical polyadic decomposition of tensor is to approximate or express the tensor by sum of rank-1 tensors. When all or almost all components of factor matrices of the tensor are highly collinear, the decomposition becomes difficult. Algorithms, e.g., the alternating algorithms, require plenty of iterations, andmay get stuck in false localminima. This paper proposes a novel method for such decompositions. The method injects one or a few rank-1 tensors into the data tensor in order to control the decompositions of the rank-expanded data, while still preserving the estimation accuracy of the original tensor. To achieve this, we develop a method to automatically generate the injected tensor which satisfies a specific estimation accuracy such that this tensor should not dominate rank- 1 tensors of the data tensor, but is still able to be retrieved with a sufficient accuracy. Simulations on tensors with highly collinear factor matrices will illustrate efficiency of the proposed injecting method.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BB - Applied statistics, operational research

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GA14-13713S" target="_blank" >GA14-13713S: Tensor Decomposition Methods and Their Applications</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2016

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Proocessing

  • ISBN

    978-1-4799-9987-3

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    2549-2553

  • Publisher name

    IEEE

  • Place of publication

    Piscataway

  • Event location

    Shanghai

  • Event date

    Mar 20, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article