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Bibliografie

A. Cichocki

  1. Tichavský Petr, Phan A. H., Cichocki A. :  Krylov-Levenberg-Marquardt Algorithm for Structured Tucker Tensor Decompositions , IEEE Journal on Selected Topics in Signal Processing vol.15, 3 (2021), p. 550-559 [2021] Download Download DOI: 10.1109/JSTSP.2021.3059521
  2. Phan A. H., Cichocki A., Uschmajew A., Tichavský Petr, Luta G. :  Tensor Networks for Latent Variable Analysis: Novel Algorithms for Tensor Train Approximation , IEEE Transactions on Neural Networks and Learning Systems vol.31, 11 (2020), p. 4622-4636 [2020] Download Download DOI: 10.1109/TNNLS.2019.2956926
  3. Tichavský Petr, Phan A. H., Cichocki A. :  Sensitivity in tensor decomposition , IEEE Signal Processing Letters vol.26, 11 (2019), p. 1653-1657 [2019] Download Download DOI: 10.1109/LSP.2019.2943060

  1. Phan A. H., Tichavský Petr, Sobolev K., Sozykin K., Ermilov D., Cichocki A. :  Canonical polyadic tensor decomposition with low-rank factor matrices , ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), p. 4690-4694, IEEE International Conference on Acoustics, Speech, and Signal Processing 2021, (Toronto, CA, 20210606) [2021] Download DOI: 10.1109/ICASSP39728.2021.9414606
  2. 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, p. 522-539 , Eds: Vedaldi Andrea, Bischof Horst, Brox Thomas, Frahm Jan-Michael, European Conference on Computer Vision 2020 /16./, (Glasgow, GB, 20200823) [2020] Download DOI: 10.1007/978-3-030-58526-6_31
  3. 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, p. 3917-3921, 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2020, (Barcelona, ES, 20200504) [2020] Download DOI: 10.1109/ICASSP40776.2020.9054312