My second PhD was about Canonical Polyadic Decomposition (aka CPD aka Candecom/Parafac aka CP decomposition). The papers below are about CPD, multi-linear SVD, decomposition into a sum of multilinear rank-
terms, and block-term tensor decomposition.
Work in progress
- I. Domanov and L. De Lathauwer. Decomposition of a tensor into multilinear rank-
terms, arXiv:1808.02423.(submitted)
- I. Domanov, N. Vervliet, and L. De Lathauwer. Decomposition of a tensor into multilinear rank-
terms, Internal Report 18-51, ESAT-STADIUS, KU Leuven (Leuven, Belgium), 2018.(current version)
- I. Domanov and L. De Lathauwer. On the similarity of tensors with column equivalent matrix unfoldings, Internal Report 18-70, ESAT-STADIUS, KU Leuven (Leuven, Belgium), 2018.
Publications in journals
- M. Sørensen, I. Domanov, and L. De Lathauwer. Coupled canonical polyadic decompositions and multiple shift-invariance in array processing, IEEE Transactions on Signal Processing, 66(14):3665-3680, 2018.
- M. Boussé, N. Vervliet, I. Domanov, O. Debals, and L. De Lathauwer. Linear Systems with a Canonical Polyadic Decomposition Constrained Solution: Algorithms and Applications, Numer Linear Algebra Appl., 2018 (published online).
- I. Domanov, A. Stegeman, and L. De Lathauwer. On the largest multilinear singular values of higher-order tensors, SIAM J. Matrix Anal. Appl., 38(4):1434-1453, 2017.
- I. Domanov and L. De Lathauwer. Canonical polyadic decomposition of third-order tensors: relaxed uniqueness conditions and algebraic algorithm, Lin. Alg. Appl., 513, 342-375,2017.
- I. Domanov and L. De Lathauwer. Generic uniqueness of a structured matrix factorization and applications in blind source separation, IEEE Journal of Selected Topics in Signal Processing, 10(4):701-711, 2016.
- L. Sorber, I. Domanov, M. Van Barel, and L. De Lathauwer. Exact Line and Plane Search for Tensor Optimization, Computational Optimization and Applications, 63(1):121-142, 2016.
- I. Domanov and L. De Lathauwer., Generic uniqueness conditions for the canonical polyadic decomposition and INDSCAL, SIAM J. Matrix Anal. Appl., 36(4):1567-1589, 2015.
- M. Sørensen, I. Domanov, and L. De Lathauwer. Coupled Canonical Polyadic Decompositions and (Coupled) Decompositions in Multilinear rank-
terms — Part II: Algorithms, SIAM J. Matrix Anal. Appl., 36(3):1015-1045, 2015.
- I. Domanov and L. De Lathauwer. Canonical polyadic decomposition of third-order tensors: reduction to generalized eigenvalue decomposition, SIAM J. Matrix Anal. Appl., 35(2):636-660, 2014.
- I. Domanov and L. De Lathauwer. On the Uniqueness of the Canonical Polyadic Decomposition of third-order tensors — Part II: Uniqueness of the overall decomposition, SIAM J. Matrix Anal. Appl., 34(3):876-903, 2013.
- I. Domanov and L. De Lathauwer. On the Uniqueness of the Canonical Polyadic Decomposition of third-order tensors — Part I: Basic Results and Uniqueness of One Factor Matrix, SIAM J. Matrix Anal. Appl., 34(3):855-875, 2013.
PhD thesis II
I. Domanov. Study of Canonical Polyadic Decomposition of Higher-Order Tensors, PhD thesis, Faculty of Engineering, KU Leuven (Leuven, Belgium), Sep 2013, 143p.
Publications in proceedings
- I. Domanov and L. De Lathauwer. Enhanced Line Search for Blind Channel Identification Based on the Parafac Decomposition of Cumulant Tensors, in Proc. of the 19th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2010), Budapest, Hungary, Jul. 2010, pp. 1001-1002.
- I. Domanov and L. De Lathauwer. Blind Channel Identification of MISO Systems Based on the CP Decomposition of Cumulant Tensors, in Proc. of the 2011 European Signal Processing Conference (EUSIPCO 2011), Barcelona, Spain, Aug.-Sep. 2011, pp. 2215-2218.