Search results

  1. 1.
    0541614 - ÚTIA 2022 RIV US eng J - Journal Article
    Tichavský, Petr - Phan, A. H. - Cichocki, A.
    Krylov-Levenberg-Marquardt Algorithm for Structured Tucker Tensor Decompositions.
    IEEE Journal on Selected Topics in Signal Processing. Roč. 15, č. 3 (2021), s. 550-559. ISSN 1932-4553. E-ISSN 1941-0484
    Grant - others:GA ČR(CZ) GA20-17720S
    Institutional support: RVO:67985556
    Keywords : canonical polyadic tensor decomposition * parallel factor analysis * tensor chain * sensitivity
    OECD category: Electrical and electronic engineering
    Impact factor: 7.695, year: 2021
    Method of publishing: Limited access
    http://library.utia.cas.cz/separaty/2021/SI/tichavsky-0541614.pdf https://ieeexplore.ieee.org/document/9354901
    Permanent Link: http://hdl.handle.net/11104/0319267
     
     
  2. 2.
    0518308 - ÚTIA 2021 RIV US eng J - Journal Article
    Phan, A. H. - Cichocki, A. - Uschmajew, A. - Tichavský, Petr - Luta, G. … Total 6 authors
    Tensor Networks for Latent Variable Analysis: Novel Algorithms for Tensor Train Approximation.
    IEEE Transactions on Neural Networks and Learning Systems. Roč. 31, č. 11 (2020), s. 4622-4636. ISSN 2162-237X. E-ISSN 2162-2388
    R&D Projects: GA ČR GA17-00902S
    Institutional support: RVO:67985556
    Keywords : Blind source separation * tensor network (TN) * image denoising * nested Tucker * tensor train (TT) decomposition * Tucker-2 (TK2) decomposition * truncated singular value decomposition (SVD)
    OECD category: Electrical and electronic engineering
    Impact factor: 10.451, year: 2020
    Method of publishing: Limited access
    http://library.utia.cas.cz/separaty/2020/SI/tichavsky-0518308.pdf https://ieeexplore.ieee.org/document/8984730
    Permanent Link: http://hdl.handle.net/11104/0303994
     
     
  3. 3.
    0509948 - ÚTIA 2020 RIV US eng J - Journal Article
    Tichavský, Petr - Phan, A. H. - Cichocki, A.
    Sensitivity in tensor decomposition.
    IEEE Signal Processing Letters. Roč. 26, č. 11 (2019), s. 1653-1657. ISSN 1070-9908. E-ISSN 1558-2361
    R&D Projects: GA ČR GA17-00902S
    Institutional support: RVO:67985556
    Keywords : PARAFAC * convolutive neural networks * tensor
    OECD category: Electrical and electronic engineering
    Impact factor: 3.105, year: 2019
    Method of publishing: Limited access
    http://library.utia.cas.cz/separaty/2019/SI/tichavsky-0509948.pdf https://ieeexplore.ieee.org/document/8846103
    Permanent Link: http://hdl.handle.net/11104/0301141
     
     


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