Search results

  1. 1.
    0545875 - ÚTIA 2022 RIV CH eng C - Conference Paper (international conference)
    Plajner, Martin - Vomlel, Jiří
    Bayesian Networks for the Test Score Prediction: A Case Study on a Math Graduation Exam.
    Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2021.. Cham: Springer, 2021 - (Vejnarová, J.; Wilson, N.), s. 255-267. Lecture Notes in Computer Science, Vol 12897. ISBN 978-3-030-86771-3. ISSN 0302-9743. E-ISSN 1611-3349.
    [ECSQARU 2021 : Symbolic and Quantitative Approaches to Reasoning with Uncertainty. Praha (CZ), 21.09.2021-24.09.2021]
    R&D Projects: GA ČR(CZ) GA19-04579S
    Institutional support: RVO:67985556
    Keywords : Bayesian networks * Educational testing * Score prediction * Efficient probabilistic inference * Multidimensional IRT * CP tensor decomposition
    OECD category: Robotics and automatic control
    http://library.utia.cas.cz/separaty/2021/MTR/plajner-0545875.pdf
    Permanent Link: http://hdl.handle.net/11104/0323622
     
     
  2. 2.
    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
     
     
  3. 3.
    0534541 - ÚTIA 2021 RIV GB eng C - Conference Paper (international conference)
    Phan, A. H. - Sobolev, K. - Sozykin, K. - Ermilov, D. - Gusak, J. - Tichavský, Petr - Glukhov, V. - Oseledets, I. - Cichocki, A.
    Stable Low-Rank Tensor Decomposition for Compression of Convolutional Neural Network.
    ECCV 2020. Cham: Springer Nature Switzerland AG 2020, 2020 - (Vedaldi, A.; Bischof, H.; Brox, T.; Frahm, J.), s. 522-539. Lecture Notes in Computer Science, LNCS, 12374. ISBN 978-3-030-58525-9. ISSN 0302-9743. E-ISSN 1611-3349.
    [European Conference on Computer Vision 2020 /16./. Glasgow (GB), 23.08.2020-28.08.2020]
    Institutional support: RVO:67985556
    Keywords : Convolutional neural network acceleration * Low-rank tensor decomposition * Degeneracy correction
    OECD category: Electrical and electronic engineering
    http://library.utia.cas.cz/separaty/2020/SI/tichavsky-0534541.pdf
    Permanent Link: http://hdl.handle.net/11104/0313191
     
     
  4. 4.
    0523836 - ÚTIA 2021 RIV US eng C - Conference Paper (international conference)
    Tichavský, Petr - Phan, A. H. - Cichocki, A.
    Weighted Krylov-Levenberg-Marquardt method for canonical polyadic tensor decomposition.
    2020 IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2020. Piscataway: IEEE, 2020, s. 3917-3921. ISBN 978-1-5090-6631-5.
    [2020 IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2020. Barcelona (ES), 04.05.2020-08.05.2020]
    R&D Projects: GA ČR GA17-00902S
    Institutional support: RVO:67985556
    Keywords : Tensor decomposition * tensor completion * PARAFAC
    OECD category: Statistics and probability
    http://library.utia.cas.cz/separaty/2020/SI/tichavsky-0523836.pdf
    Permanent Link: http://hdl.handle.net/11104/0308330
     
     
  5. 5.
    0500107 - ÚTIA 2020 RIV US eng J - Journal Article
    Phan, A. H. - Tichavský, Petr - Cichocki, A.
    Error Preserving Correction: A Method for CP Decomposition at a Target Error Bound.
    IEEE Transactions on Signal Processing. Roč. 67, č. 5 (2019), s. 1175-1190. ISSN 1053-587X. E-ISSN 1941-0476
    R&D Projects: GA ČR GA17-00902S
    Institutional support: RVO:67985556
    Keywords : Canonical polyadic decomposition * parallel factor analysis * tensor decomposition
    OECD category: Statistics and probability
    Impact factor: 5.028, year: 2019
    Method of publishing: Limited access
    http://library.utia.cas.cz/separaty/2019/SI/tichavsky-0500107.pdf https://ieeexplore.ieee.org/document/8579207
    Permanent Link: http://hdl.handle.net/11104/0293323
     
     
  6. 6.
    0493355 - ÚTIA 2019 RIV CZ eng K - Conference Paper (Czech conference)
    Tichavský, Petr - Vomlel, Jiří
    Representations of Bayesian Networks by Low-Rank Models.
    Proceedings of Machine Learning Research. Vol. 72. Praha: UTIA, 2018 - (Kratochvíl, V.; Studený, M.), s. 463-472. E-ISSN 1938-7228.
    [International Conference on Probabilistic Graphical Models. Praha (CZ), 11.09.2018-14.09.2018]
    R&D Projects: GA ČR GA17-00902S
    Institutional support: RVO:67985556
    Keywords : canonical polyadic tensor decomposition * conditional probability tables * marginal probability tables
    OECD category: Statistics and probability
    http://library.utia.cas.cz/separaty/2018/SI/tichavsky-0493355.pdf
    Permanent Link: http://hdl.handle.net/11104/0286997
     
     
  7. 7.
    0483430 - ÚTIA 2018 RIV US eng C - Conference Paper (international conference)
    Tichavský, Petr - Phan, A. H. - Cichocki, A.
    Under-Determined Tensor Diagonalization for Decomposition of Difficult Tensors.
    IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) 2017. Piscataway: IEEE, 2017, s. 263-266. ISBN 978-1-5386-1250-7.
    [CAMSAP 2017 - 7th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing. Curacao (NL), 10.12.2017-13.12.2017]
    R&D Projects: GA ČR GA17-00902S
    Institutional support: RVO:67985556
    Keywords : canonical polyadic decomposition * tensor decomposition * matrix multiplication
    OECD category: Statistics and probability
    http://library.utia.cas.cz/separaty/2017/SI/tichavsky-0483430.pdf
    Permanent Link: http://hdl.handle.net/11104/0278758
     
     
  8. 8.
    0472586 - ÚTIA 2018 RIV US eng C - Conference Paper (international conference)
    Phan, A. H. - Tichavský, Petr - Cichocki, A.
    Partitioned Hierarchical Alternating Least Squares Algorithm for CP Tensor Decomposition.
    2017 IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2017. New Orleans: IEEE, 2017, s. 2542-2546. ISBN 978-1-5090-4116-9.
    [2017 IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2017. New Orleans (US), 05.03.2017-09.03.2017]
    R&D Projects: GA ČR GA17-00902S
    Institutional support: RVO:67985556
    Keywords : tensor decomposition * canonical polyadic decomposition * PARAFAC * alternating least squares
    OECD category: Statistics and probability
    http://library.utia.cas.cz/separaty/2017/SI/tichavsky-0472586.pdf
    Permanent Link: http://hdl.handle.net/11104/0271355
     
     
  9. 9.
    0468385 - ÚTIA 2018 RIV NL eng J - Journal Article
    Tichavský, Petr - Phan, A. H. - Cichocki, A.
    Numerical CP Decomposition of Some Difficult Tensors.
    Journal of Computational and Applied Mathematics. Roč. 317, č. 1 (2017), s. 362-370. ISSN 0377-0427. E-ISSN 1879-1778
    R&D Projects: GA ČR(CZ) GA14-13713S
    Institutional support: RVO:67985556
    Keywords : Small matrix multiplication * Canonical polyadic tensor decomposition * Levenberg-Marquardt method
    OECD category: Applied mathematics
    Impact factor: 1.632, year: 2017
    http://library.utia.cas.cz/separaty/2017/SI/tichavsky-0468385.pdf
    Permanent Link: http://hdl.handle.net/11104/0270594
     
     
  10. 10.
    0460710 - ÚTIA 2017 RIV US eng J - Journal Article
    Tichavský, Petr - Phan, A. H. - Cichocki, A.
    Partitioned Alternating Least Squares Technique for Canonical Polyadic Tensor Decomposition.
    IEEE Signal Processing Letters. Roč. 23, č. 7 (2016), s. 993-997. ISSN 1070-9908. E-ISSN 1558-2361
    R&D Projects: GA ČR(CZ) GA14-13713S
    Institutional support: RVO:67985556
    Keywords : canonical polyadic decomposition * PARAFAC * tensor decomposition
    Subject RIV: BB - Applied Statistics, Operational Research
    Impact factor: 2.528, year: 2016
    http://library.utia.cas.cz/separaty/2016/SI/tichavsky-0460710.pdf
    Permanent Link: http://hdl.handle.net/11104/0261531
     
     

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