Edited Books

  1. De Lathauwer L., Comon P., Mastronardi N., (eds.), Special Issue: Tensor Decompositions and Applications, vol. 30 of SIAM Journal on Matrix Analysis and Applications, Society for Industrial and Applied Mathematics (Philadelphia, Pennssylvania), 2008, 430 p.

  2. De Lathauwer L., Comon P., (eds.), Blind source separation and multichannel deconvolution, Special Issue Signal Processing, vol. 73 of Signal Processing, Elsevier, 1999, 190 p.

Contributions to books

  1. Van Eeghem F., De Lathauwer L., "Tensor similarity in chemometrics", in Chapter 2.16 of Comprehensive Chemometrics: Chemical and Biochemical Data Analysis, (Brown S., Tauler R., and Walczak B., eds.), Elsevier, 2020, pp. 337--354.

  2. Padhy S., Goovaerts G., Bousse M., De Lathauwer L., Van Huffel S., "The Power of Tensor-Based Approaches in Cardiac Applications", in Chapter Biomedical Signal Processing: Advances in Theory, Algorithms and Applications, (Naik Ganesh R., ed.), Springer Singapore, 2020, pp. 291-323.

  3. Vervliet N., De Lathauwer L., "Numerical optimization-based algorithms for data fusion", in Chapter 4 of Data Fusion Methodology and Applications, (Cocchi M., ed.), vol. 33 of mph{Data Handling in Science and Technology}, Elsevier, 2019, pp. 81-128.

  4. Comon P., De Lathauwer L., "Algebraic Identification of Underdetermined Mixtures", in Chapter 9 of Handbook of Blind Source Separation. Independent Component Analysis and Applications, (Comon P., and Jutten C., eds.), Academic Press (Oxford, United Kingdom), 2010, pp. 325-365.

  5. De Lathauwer L., "Algebraic Methods after Prewhitening", in Chapter 5 of Handbook of Blind Source Separation. Independent Component Analysis and Applications, (Comon P., and Jutten C., eds.), Academic Press (Oxford, United Kingdom), 2010, pp. 155-177.

  6. De Lathauwer L., "Algorithmes avec Blanchiment Utilisant le Cumulant d'Ordre Elev݊Submitted:", in Chapter 5 of Sްaration de Sources, (Comon P., and Jutten C., eds.), vol. 1 of mph{Sްaration de Sources}, Hermes (Paris, France), 2007, pp. 169-196.

  7. De Vos M., De Lathauwer L., Van Huffel S., "Decomposition methods in neuroscience", in Chapter 1 of Recent Advances in Biomedical Signal Processing, (Gorriz J.M., and and Lang E.W. and Ramirez J., eds.), Bentham Publishers (Bussum, Nederland), 2010, pp. 1-25.

International Journal Papers

  1. Hautecoeur C., De Lathauwer L., Gillis N., Glineur F., "Least-squares methods for nonnegative matrix factorization over rational functions", IEEE Transactions on Signal Processing, vol. 71, Apr. 2023, pp. 1712-1724.

  2. Ashtari P., Sima D., De Lathauwer L., Sappey-Marinier D., Maes F., Van Huffel S., "Factorizer : A scalable interpretable approach to context modeling for medical image segmentation", Medical Image Analysis, vol. 84, Feb. 2023, pp. 1-16 (102706).

  3. Govindarajan N., Widdershoven R., Chandrasekaran S., De Lathauwer L., "A fast algorithm for computing Macaulay nullspaces of bivariate polynomial systems", SIAM Journal on Matrix Analysis and Applications, vol. 45, no. 1, Jan. 2024, pp. 368-396.

  4. Hendrikx S., Widdershoven R., Vervliet N., De Lathauwer L., "Tensorlab+: A case study on reproducibility in tensor research", IEEE Computing in Science and Engineering, vol. 25, no. 5, Sep. 2023, pp. 6--13.

  5. Evert E., De Lathauwer L., "On best low rank approximation of positive definite tensors", SIAM Journal on Matrix Anal. Appl., vol. 44, no. 2, 2023, pp. 867-893.

  6. Ayvaz M., De Lathauwer L., "CPD-Structured Multivariate Polynomial Optimization", Frontiers in Applied Mathematics and Statistics, 8:836433, vol. 8, Mar. 2022, pp. 1-24.

  7. Hendrikx S., De Lathauwer L., "Block row Kronecker-structured linear systems with a low-rank tensor solution", Frontiers in Applied Mathematics and Statistics, Special Issue on High-Performance Tensor Computations in Scientific Computing and Data Science, vol. 8, Mar. 2022, pp. 1-30.

  8. Evert E., Vandecappelle M., De Lathauwer L., "Canonical Polyadic Decomposition via the generalized Schur decomposition", IEEE Signal Processing Letters, vol. 29, Mar. 2022, pp. 937-941.

  9. Vandecappelle M., De Lathauwer L., "Updating the multilinear UTV decomposition", Transactions on Signal Processing, vol. 70, no. 1053-587X, Jul. 2022, pp. 3551-3565.

  10. Vandecappelle M., De Lathauwer L., "From multilinear SVD to multilinear UTV decomposition", Signal Processing, vol. 198, Sep. 2022, pp. 1--6.

  11. Bellemans I., Vervliet N., De Lathauwer L., Moelans N., Verbeken K., "Towards more realistic simulations of microstructural evolution in oxidic systems", Calphad, Special Issue on 11th International Conference on Molten Slags, Fluxes and Salts (MOLTEN 2021), vol. 77, no. 102402, Apr. 2022, pp. 1-14 (art nb 102402).

  12. Govindarajan N., Epperly E., De Lathauwer L., "(Lr, Lr,1)-Decompositions, sparse component analysis, and the blind separation of sums of exponentials", SIAM journal on matrix analysis and applications, vol. 43, no. 2, Jun. 2022, pp. 912-938.

  13. Govindarajan N., Vervliet N., De Lathauwer L., "Regression and classification with spline-based separable expansions", Frontiers in Big Data, vol. 5, Feb. 2022, pp. 1-19.

  14. Chatzichristos C., Kofidis E., De Lathauwer L., Theodoridis S., Van Huffel S., "Early soft and flexible fusion of electroencephalography and functional magnetic resonance imaging via double coupled matrix tensor factorization for multisubject group analysis.", Human Brain mapping, vol. 43, no. 4, Mar. 2022, pp. 1231-1255.

  15. Evert E., Vandecappelle M., De Lathauwer L., "A recursive eigenspace computation for the canonical polyadic decomposition", SIAM Journal on Matrix Analysis and Applications, vol. 43, no. 1, Feb. 2022, pp. 274-300.

  16. Vandecappelle M., Vervliet N., De Lathauwer L., "Inexact generalized Gauss–Newton for scaling the canonical polyadic decomposition with non-least-squares cost functions", Journal of Selected Topics in Signal Processing, Special Issue on Tensor Decomposition for Signal Processing and Machine Learning, vol. 15, no. 3, Apr. 2021, pp. 491-505.

  17. Fu X., Vervliet N., De Lathauwer L., Huang K., Gillis N., "Computing Large-Scale Matrix and Tensor Decomposition With Structured Factors: A Unified Nonconvex Optimization Perspective", IEEE Signal Processing Magazine, Special Issue on Nonconvex Optimization for Signal Processing and Machine Learning, vol. 37, no. 5, Sep. 2020, pp. 78-94.

  18. Evert E., De Lathauwer L., "Guarantees for existence of a best canonical polyadic approximation of a noisy low-rank tensor", SIAM Journal on Matrix Analysis and Applications, vol. 43, no. 1, Mar. 2022, pp. 328-369.

  19. Berger G.O., Absil P.A., De Lathauwer L., Jungers R.M., Van Barel M., "Equivalent polyadic decompositions of matrix multiplication tensors", Journal of Computational and Applied Mathematics, vol. 406, May 2022, 113941 p.

  20. Coutinho Y., Vervliet N., De Lathauwer L., Moelans N., "Combining thermodynamics with tensor completion techniques to enable multicomponent microstructure prediction", npj Computational Materials, vol. 6, no. 2, Jan. 2020, pp. 1-10.

  21. Vandecappelle M., Vervliet N., De Lathauwer L., "A second-order method for fitting the canonical polyadic decomposition with non-least-squares cost", Transactions on Signal Processing, vol. 68, Aug. 2020, pp. 4454-4465.

  22. Sorensen M., De Lathauwer L., Sidiropoulos N., "Bilinear factorizations subject to monomial equality constraints via tensor decompositions", Linear Algebra and its Applications, vol. 621, Jul. 2021, pp. 296-333.

  23. Gong X.-F., Lin Q.-H., Cong F.-Y., De Lathauwer L., "Double Coupled Canonical Polyadic Decomposition of Third-Order Tensors: Algebraic Algorithm and Relaxed Uniqueness Conditions", Signal Processing: Image Communications, Special Issue on Tensor Image Processing, vol. 73, Apr. 2019, pp. 22-36.

  24. Domanov I., De Lathauwer L., "From computation to comparison of tensor decompositions", SIAM Journal on Matrix Analysis and Applications (SIMAX), vol. 42, no. 2, Apr. 2021, pp. 449-474.

  25. Domanov I., De Lathauwer L., "On uniqueness and computation of the decomposition of a tensor into multilinear rank-$(1,L_r,L_r)$ terms", SIAM Journal on Matrix Analysis and Applications (SIMAX), vol. 41, no. 2, May 2020, pp. 747-803.

  26. Vanderstukken J., Kurschner P., Domanov I., De Lathauwer L., "Systems of polynomial equations, higher-order tensor decompositions and multidimensional harmonic retrieval: A unifying framework. Part II: The block-term decomposition", SIAM Journal on Matrix Analysis and Applications, vol. 42, no. 2, Jun. 2021, pp. 913-953.

  27. Vanderstukken J., De Lathauwer L., "Systems of polynomial equations, higher-order tensor decompositions and multidimensional harmonic retrieval: A unifying framework. Part I: The canonical polyadic decomposition", SIAM Journal on Matrix Analysis and Applications, vol. 42, no. 2, Jun. 2021, pp. 883-912.

  28. Stegeman A., De Lathauwer L., "Rayleigh quotient methods for estimating common roots of noisy univariate polynomials", Computational Methods in Applied Mathematics, Special Issue on Tensor numerical methods: Theoretical Analysis and Modern Applications, Jul. 2018, pp. 1-27.

  29. Sorensen M., Domanov I., De Lathauwer L., "Coupled canonical polyadic decompositions and multiple shift-invariance in array processing", IEEE Transactions on Signal Processing, vol. 66, no. 14, Jul. 2018, pp. 3665-3680.

  30. Van Eeghem F., Debals O., Vervliet N., De Lathauwer L., "Coupled and incomplete tensors in blind system identification", IEEE Transactions on Signal Processing, vol. 66, no. 23, Oct. 2018, pp. 6137-6147.

  31. Van Eeghem F., Debals O., De Lathauwer L., "Tensor similarity in two modes", IEEE Transactions on Signal Processing, vol. 66, no. 5, Mar. 2018, pp. 1273 - 1285.

  32. Bharath H.N., Debals O., Sima D.M., Himmelreich U., De Lathauwer L., Van Huffel S., "Tensor-Based Method for Residual Water Suppression in 1H Magnetic Resonance Spectroscopic Imaging", IEEE Transactions on Biomedical Engineering, vol. 66, no. 2, Feb. 2019, pp. 584-594.

  33. Delrue S., Aleshin V., Sorensen M., De Lathauwer L., "Simulation study of the localization of a near-surface crack using an air-coupled ultrasonic sensor array", Sensors, vol. 17, no. 4, Apr. 2017, pp. 1-21.

  34. Debals O., Van Barel M., De Lathauwer L., "Non-negative Matrix Factorization using Non-negative Polynomial Approximations", IEEE Signal Processing Letters, vol. 24, no. 7, Jul. 2017, pp. 948-952.

  35. Gong X., Lin Q., Cong F., De Lathauwer L., "Double coupled canonical polyadic decomposition for joint blind source separation", IEEE Transactions on Signal Processing, vol. 66, no. 13, Jul. 2018, pp. 3475-3490.

  36. Bousse M., Vervliet N., Domanov I., Debals O., De Lathauwer L., "Linear Systems with a Canonical Polyadic Decomposition Constrained Solution: Algorithms and Applications", Numerical Linear Algebra with Applications, Special Issue on Matrix Equations and Tensor Techniques, vol. 25, no. 6, Aug. 2018, pp. 1-18.

  37. Domanov I., Stegeman A., De Lathauwer L., "On the largest multilinear singular values of higher-order tensors", SIAM Journal on Matrix Analysis and Applications, vol. 38, no. 4, Nov. 2017, pp. 1434-1453.

  38. Vervliet N., Debals O., De Lathauwer L., "Exploiting efficient representations in large-scale tensor", SIAM Journal on Scientific Computing, vol. 41, no. 2, Mar. 2019, pp. A789--A815.

  39. Bousse M., Debals O., De Lathauwer L., "Tensor-based large-scale blind system identification using segmentation", IEEE Transactions on Signal Processing, vol. 65, no. 21, Nov. 2017, pp. 5770-5784.

  40. Van Eeghem F., De Lathauwer L., "Algorithms for canonical polyadic decomposition with block-circulant factors", IEEE Signal Processing Letters, vol. 25, no. 6, Jun. 2018, pp. 798-802.

  41. Bharath H.N., Sima D.M., Sauwen N., Himmelreich U., De Lathauwer L., Van Huffel S., "Non-Negative Canonical Polyadic Decomposition for Tissue Type Differentiation in Gliomas", IEEE Journal of Biomedical and Health Informatics, vol. 21, no. 4, Jul. 2017, pp. 1124-1132.

  42. Van Eeghem F., Sorensen M., De Lathauwer L., "Tensor decompositions with several block-Hankel factors and application in blind system identification", IEEE Transactions on Signal Processing, vol. 65, no. 15, Aug. 2017, pp. 4090-4101.

  43. Sorensen M. Van Eeghem F., De Lathauwer L., "Blind multichannel deconvolution and convolutive extensions of canonical polyadic and block term decompositions", IEEE Transactions on signal processing, vol. 65, no. 15, Aug. 2017, pp. 4132-4145.

  44. Sidiropoulos N., De Lathauwer L., Fu X., Huang K., Papalexakis E., Faloutsos C., "Tensor Decomposition for Signal Processing and Machine Learning", IEEE Transactions on Signal Processing, vol. 65, no. 13, Jul. 2017, pp. 3551-3582.

  45. Sorensen M., De Lathauwer L., "Fiber sampling approach to canonical polyadic decomposition and application to tensor completion", SIAM Journal on Matrix Analysis and Applications, vol. 40, no. 3, Jul. 2019, pp. 888-917.

  46. Sorensen M., De Lathauwer L., "Multidimensional Harmonic Retrieval via Coupled Canonical Polyadic Decomposition - Part II: Algorithm and Multirate Sampling", IEEE Transactions on Signal Processing, vol. 65, no. 2, Jan. 2017, pp. 528-539.

  47. Sorensen M., De Lathauwer L., "Multidimensional Harmonic Retrieval via Coupled Canonical Polyadic Decomposition - Part I: Model and Identifiability", IEEE Transactions on Signal Processing,, vol. 65, no. 2, Jan. 2017, pp. 517-527.

  48. Vervliet N., De Lathauwer L., "A randomized block sampling approach to canonical polyadic decomposition of large-scale tensors", IEEE Journal of Selected Topics in Signal Processing, vol. 10, no. 2, 2016, pp. 284-295.

  49. Bousse M., Debals O., De Lathauwer L., "A Tensor-Based Method for Large-Scale Blind Source Separation using Segmentation", IEEE Transactions on Signal Processing, vol. 65, no. 2, Jan. 2017, pp. 346--358.

  50. Debals O., Van Barel M., De Lathauwer L., "Löwner-based Blind Signal Separation of Rational Functions with Applications", IEEE Transactions in Signal Processing, vol. 64, no. 8, Apr. 2016, pp. 1909-1918.

  51. Domanov I., De Lathauwer L., "Generic uniqueness of a structured matrix factorization and applications in blind source separation", IEEE Journal of Selected Topics in Signal Processing, vol. 10, no. 4, Jun. 2016, pp. 701-711.

  52. Domanov I., De Lathauwer L., "Canonical polyadic decomposition of third-order tensors: relaxed uniqueness conditions and algebraic algorithm", Linear Algebra and its Applications, vol. 513, Jan. 2017, pp. 342-375.

  53. Domanov I. and De Lathauwer L., "Generic uniqueness conditions for the canonical polyadic decomposition and INDSCAL", SIAM Journal on Matrix Analysis and Applications (SIMAX), vol. 36, no. 4, Nov. 2015, pp. 1567-1589.

  54. Cichocki A., Mandic D., Phan A.-H., Caiafa C., Zhou G., Zhao Q., De Lathauwer L., "Tensor Decompositions for Signal Processing Applications. From Two-way to Multiway Component Analysis", IEEE Signal Processing Magazine, vol. 32, no. 2, Mar. 2015, pp. 145-163.

  55. Hunyadi B., Camps D., Sorber L., Van Paesschen W., De Vos M., Van Huffel S., De Lathauwer L., "Block term decomposition for modelling epileptic seizures", EURASIP Journal on Advances in Signal Processing, Special Issue on Recent Advances in Tensor Based Signal and Image Processing, vol. 2014, no. 139, Sep. 2014, pp. .

  56. Vervliet N., Debals O., Sorber L., De Lathauwer L., "Breaking the Curse of Dimensionality Using Decompositions of Incomplete Tensors: Tensor-based scientific computing in big data analysis", Signal Processing Magazine, IEEE, vol. 31, no. 5, Sep. 2014, pp. 71--79.

  57. Sorensen M., De Lathauwer L., "Multiple Invariance ESPRIT for Nonuniform Linear Arrays: A Coupled Canonical Polyadic Decomposition Approach", IEEE TRANSACTIONS ON SIGNAL PROCESSING, vol. 64, no. 14, Jul. 2016, pp. 3693 - 3704.

  58. Sorber L., Van Barel M., De Lathauwer L., "Structured data fusion", IEEE Journal of Selected Topics in Signal Processing, vol. 9, no. 4, Jun. 2015, pp. 586-600.

  59. Sorensen M., Domanov I., De Lathauwer L., "Coupled Canonical Polyadic Decompositions and (Coupled) Decompositions in Multilinear rank-(L_r,n,L_r,n,1) terms --- Part II: Algorithms", SIAM Journal on Matrix Analysis and Applications, vol. 36, no. 3, Jul. 2015, pp. 1015-1045.

  60. Sorensen M., De Lathauwer L., "Coupled Canonical Polyadic Decompositions and (Coupled) Decompositions in Multilinear rank-(L_r,n,L_r,n,1) terms --- Part I: Uniqueness", SIAM Journal on Matrix Analysis and Applications, vol. 36, no. 2, Apr. 2015, pp. 496 - 522.

  61. Sorber L., Van Barel M., De Lathauwer L., "Numerical solution of bivariate and polyanalytic polynomial systems", SIAM Journal on Numerical Analysis, vol. 52, no. 4, 2014, pp. 1551-1572.

  62. Domanov I., De Lathauwer L., "Canonical polyadic decomposition of third-order tensors: reduction to generalized eigenvalue decomposition", SIAM Journal on Matrix Analysis and Applications (SIMAX), vol. 35, no. 2, Apr.-May 2014, pp. 636--660.

  63. Sorensen M., De Lathauwer L., "New Uniqueness Conditions for the Canonical Polyadic Decomposition of Third-Order Tensors", SIAM Journal on Matrix Analysis and Applications, vol. 36, no. 4, Oct. 2015, pp. 1381-1403.

  64. Sorber L., Domanov I., Van Barel M., De Lathauwer L., "Exact Line and Plane Search for Tensor Optimization", Computational Optimization and Applications, vol. 63, no. 1, Jan. 2016, pp. 121--142.

  65. Van Deun K., Van Mechelen I., Thorrez L., Schouteden M., De Moor B., van der Werf M.J., De Lathauwer L., Smilde A.K., Kiers H.A.L., "DISCO-SCA and properly applied GSVD as swinging methods to find common and distinctivve processes", PLoS One, vol. 7, no. 5, May 2012, e37840 p.

  66. Domanov I., De Lathauwer L., "On the Uniqueness of the Canonical Polyadic Decomposition of third-order tensors --- Part II: Uniqueness of the overall decomposition", SIAM Journal on Matrix Analysis and Applications (SIMAX), vol. 34, no. 3, Jul.-Sep. 2013, pp. 876-903.

  67. Domanov I., De Lathauwer L., "On the Uniqueness of the Canonical Polyadic Decomposition of third-order tensors --- Part I: Basic Results and Uniqueness of One Factor Matrix", SIAM Journal on Matrix Analysis and Applications (SIMAX), vol. 34, no. 3, Jul.-Sep. 2013, pp. 855-875.

  68. Sorber L., Van Barel M., De Lathauwer L., "Optimization-based algorithms for tensor decompositions: canonical polyadic decomposition, decomposition in rank-(Lr,Lr,1) terms and a new generalization", SIAM Journal on Optimization, vol. 23, no. 2, Apr. 2013, pp. 695-720.

  69. Sorensen M., De Lathauwer L., "Blind Signal Separation via Tensor Decomposition With Vandermonde Factor: Canonical Polyadic Decomposition", IEEE TRANSACTIONS ON SIGNAL PROCESSING, vol. 61, no. 22, Nov. 2013, pp. 5507-5519.

  70. De Lathauwer L., "Blind Separation of Exponential Polynomials and the Decomposition of a Tensor in Rank-(Lr, Lr, 1) Terms", SIAM Journal on Matrix Analysis and Applications, vol. 32, no. 4, Dec. 2011, pp. 1451-1474.

  71. Signoretto M., Tran Dinh Q., De Lathauwer L., Suykens J.A.K., "Learning with Tensors: a Framework Based on Convex Optimization and Spectral Regularization", Machine Learning, vol. 94, no. 3, Mar. 2014, pp. 303-351.

  72. Sorensen M., De Lathauwer L., Comon P., Icart S., Deneire L., "Canonical Polyadic Decomposition with a Columnwise Orthonormal Factor Matrix", SIAM Journal on Matrix Analysis and Applications, vol. 33, no. 4, Oct.-Dec. 2012, pp. 1190-1213.

  73. Karfoul A., Albera L., De Lathauwer L., "Iterative Methods for the Canonical Decomposition of Multi-way Arrays: Application to Blind Underdetermined Mixture Identification", Signal Processing, vol. 91, no. 8, Aug. 2011, pp. 1789--1802.

  74. Sorber L., Van Barel M., De Lathauwer L., "Unconstrained Optimization of Real Functions in Complex Variables", SIAM Journal on Optimization, vol. 22, no. 3, Jul. 2012, pp. 879-898.

  75. Signoretto M., Olivetti E., De Lathauwer L., Suykens J. A. K., "Classification of multichannel signals with cumulant-based kernels", IEEE Transactions on Signal Processing, vol. 60, no. 5, May 2012, pp. 2304 - 2314.

  76. Signoretto M., De Lathauwer L., Suykens J.A.K., "A Kernel-based Framework to Tensorial Data Analysis", Neural Networks, Selected Papers from ICANN 2010, vol. 24, no. 8, Oct. 2011, pp. 861-874.

  77. Sorensen M., De Lathauwer L., Icart S., Deneire L., "On Jacobi-Type Methods for Blind Equalization of Paraunitary Channels", Signal Processing, vol. 92, no. 3, Mar. 2012, pp. 617-624.

  78. Ishteva M., Absil P.-A., Van Huffel S., De Lathauwer L., "Tucker compression and local optima", Chemometrics and Intelligent Laboratory Systems, Special Issue on Multiway and Multiset Data Analysis, vol. 106, no. 1, Mar. 2011, pp. 57-64.

  79. Ishteva M., Absil P.-A., Van Huffel S., De Lathauwer L., "Best low multilinear rank approximation of higher-order tensors, based on the Riemannian trust-region scheme", SIAM Journal on Matrix Analysis and Applications, vol. 32, no. 1, Feb. 2011, pp. 115-135.

  80. Stegeman A., De Lathauwer L., "A Method to Avoid Diverging Components in the Candecomp / Parafac Model for Generic I x J x 2 Arrays", SIAM Journal on Matrix Analysis and Applications, vol. 30, no. 4, Jan. 2009, pp. 1614-1638.

  81. De Vos M., Nion D., Van Huffel S. and De Lathauwer L., "A combination of Parallel Factor and Independent Component Analysis", Signal Processing, vol. 92, Jul. 2012, pp. 2990-2999.

  82. De Vos M., De Lathauwer L., Van Huffel S., "Spatially Constrained ICA algorithms with applications in EEG processing", Signal Processing, vol. 91, no. 8, Aug. 2011, pp. 1963-1972.

  83. Comon P., ten Berge J.M.F., De Lathauwer L., Castaing J., "Generic and Typical Ranks of Multi-Way Arrays", Linear Algebra and Applications, vol. 430, no. 11-12, Jun. 2009, pp. 2997-3007.

  84. Nion D., De Lathauwer L., "Block Component Model Based Blind DS-CDMA Receivers", IEEE Transaction on Signal Processing, vol. 56, no. 11, Nov. 2008, pp. 5567-5579.

  85. Ishteva M., De Lathauwer L., Absil P.-A., Van Huffel S., "Differential-geometric Newton method for the best rank-(R1,R2,R3) approximation of tensors", Numerical Algorithms, Tributes to Gene H. Golub Part II, vol. 51, no. 2, Jun. 2009, pp. 179-194.

  86. Absil P.-A., Ishteva M., De Lathauwer L., Van Huffel S., "A geometric Newton method for Oja's vector field", Neural Computation, vol. 21, no. 5, May 2009, pp. 1415-1433.

  87. De Lathauwer L., Castaing J., "Blind Identification of Underdetermined Mixtures by Simultaneous Matrix Diagonalization", IEEE Transactions on Signal Processing, vol. 56, no. 3, Mar. 2008, pp. 1096-1105.

  88. De Lathauwer L., de Baynast A., "Blind Deconvolution of DS-CDMA Signals by Means of Decomposition in Rank-(1,L,L) Terms", IEEE Transactions on Signal Processing, vol. 56, no. 4, Apr. 2008, pp. 1562-1571.

  89. Nion D., De Lathauwer L., "An Enhanced Line Search Scheme for Complex-Valued Tensor Decompositions. Application in DS-CDMA.", Signal Processing, vol. 88, no. 3, Mar. 2008, pp. 749-755.

  90. Ishteva M., De Lathauwer L., Absil P.-A., Van Huffel S., "Dimensionality reduction for higher-order tensors: algorithms and applications", International Journal of Pure and Applied Mathematics, vol. 42, no. 3, Mar. 2008, pp. 337-343.

  91. De Lathauwer L., Nion D., "Decompositions of a Higher-Order Tensor in Block Terms --- Part III: Alternating Least Squares Algorithms", SIAM Journal on Matrix Analysis and Applications, Special Issue on Tensor Decompositions and Applications, vol. 30, no. 3, Sep. 2008, pp. 1067-1083.

  92. De Lathauwer L., "Decompositions of a Higher-Order Tensor in Block Terms --- Part II: Definitions and Uniqueness", SIAM Journal on Matrix Analysis and Applications, Special Issue on Tensor Decompositions and Applications, vol. 30, no. 3, Sep. 2008, pp. 1033-1066.

  93. De Lathauwer L., "Decompositions of a Higher-Order Tensor in Block Terms --- Part I: Lemmas for Partitioned Matrices", SIAM Journal on Matrix Analysis and Applications, Special Issue on Tensor Decompositions and Applications, vol. 30, no. 3, Sep. 2008, pp. 1022-1032.

  94. De Vos M., De Lathauwer L., Vanrumste B., Van Huffel S., Van Paesschen W., "Canonical Decomposition of ictal scalp EEG and accurate source localisation: Principles and simulation study", Computational Intelligence and Neuroscience, Special issue on EEG/MEG, vol. 2007, no. Article ID 58253, Dec. 2007, pp. 1-10.

  95. De Vos M., Vergult A., De Lathauwer L., De Clercq W., Van Huffel S., Dupont P., Palmini A., Van Paesschen W., "Canonical decomposition of ictal scalp EEG reliably detects the seizure onset zone.", Neuroimage, vol. 37, no. 3, Sep. 2007, pp. 844-854.

  96. De Lathauwer L., Castaing J., Cardoso J.-F., "Fourth-Order Cumulant Based Blind Identification of Underdetermined Mixtures", IEEE Transactions on Signal Processing, vol. 55, no. 6, Jun. 2007, pp. 2965-2973.

  97. Boyer R., De Lathauwer L., Abed-Meraim K., "Higher Order Tensor-Based Method for Delayed Exponential Fitting", IEEE Trans. Signal Processing, vol. 55, no. 6, Jun. 2007, pp. 2795-2809.

  98. Schuermans M., Lemmerling P., De Lathauwer L., Van Huffel S., "The use of total least squares data fitting in the shape from moments problem", Signal Processing, vol. 86, no. 5, May 2006, pp. 1109-1115.

  99. Papy J.M., De Lathauwer L., Van Huffel S., "A shift invariance-based order selection technique for the exponential data modelling", IEEE Signal Processing Letters, vol. 14, no. 7, Jul. 2007, pp. 473-476.

  100. Laudadio T., Pels P., De Lathauwer L., Van Hecke P., Van Huffel S., "Tissue segmentation and classification of MRSI data using Canonical Correlation Analysis", Magnetic Resonance in Medicine, vol. 54, Nov. 2005, pp. 1519-1529.

  101. De Lathauwer L., Castaing J., "Tensor-Based Techniques for the Blind Separation of DS-CDMA Signals", Signal Processing, Special Issue on Tensor Signal Processing, vol. 87, no. 2, Feb. 2007, pp. 322-336.

  102. Hoegaerts L., De Lathauwer L., Goethals I., Suykens J.A.K., Vandewalle J., De Moor B., "Efficiently Updating and Tracking the Dominant Kernel Principal Components", Neural Networks, vol. 20, no. 2, Mar. 2007, pp. 220-229.

  103. Stegeman A., ten Berge J.M.F., De Lathauwer L., "Sufficient conditions for uniqueness in Candecomp/Parafac and Indscal with random component matrices", Psychometrika, vol. 71, no. 2, Jun. 2006, pp. 219-229.

  104. Papy J.M., De Lathauwer L., Van Huffel S., "Common pole estimation in the multi-channel exponential data modelling", Signal Processing, vol. 86, 2006, pp. 846-858.

  105. De Lathauwer L., "A link between the canonical decomposition in multilinear algebra and simultaneous matrix diagonalization", SIAM Journal on Matrix Analysis and Applications, vol. 28, no. 3, Dec. 2006, pp. 642-666.

  106. Papy J.M., De Lathauwer L., Van Huffel S., "Exponential data fitting using multilinear algebra: the decimative case", Journal of Chemometrics, Special Issue in Honor of Professor Richard A. Harshman, vol. 23, no. 7-8, Jul.-Aug. 2009, pp. 341-351.

  107. Papy J.M., De Lathauwer L., Van Huffel S., "Exponential data fitting using multilinear algebra. The single-channel and the multichannel case.", Numerical Linear Algebra and Applications, vol. 12, no. 8, Oct. 2005, pp. 809-826.

  108. De Lathauwer L., "First-Order Perturbation Analysis of the Best Rank-(R_1, R_2, R_3) Approximation in Multilinear Algebra", Journal of Chemometrics, TRICAP Special Issue (B. Rayens, Ed.), vol. 18, no. 1, Jan. 2004, pp. 2-11.

  109. De Lathauwer L., Vandewalle J., "Dimensionality reduction in higher-order signal processing and rank-(R_1, R_2,...,R_N) reduction in multilinear algebra", Linear Algebra and its Applications, Special Issue on Linear Algebra in Signal and Image Processing, vol. 391, Nov. 2004, pp. 31-55.

  110. Morren G., Wolf M., Lemmerling P., Wolf U., Choi J.H., Gratton E., De Lathauwer L., Van Huffel S., "Detection of fast neuronal signals in the motor cortex from functional near infrared spectroscopy measurements using independent component analysis", Medical and Biological Engineering and Computing, vol. 42, no. 1, Jan. 2004, pp. 92-99.

  111. Chen B., Petropulu A., De Lathauwer L., "Blind identification of convolutive MIMO systems with 3 sources and 2 sensors", Applied Signal Processing, Special Issue Space-Time Coding and Its Applications - Part II, vol. 2002, no. 5, May 2002, pp. 487-496.

  112. De Lathauwer L., De Moor B., Vandewalle J., "Computation of the Canonical Decomposition by Means of a Simultaneous Generalized Schur Decomposition", SIAM Journal on Matrix Analysis and Applications, vol. 26, no. 2, 2004, pp. 295-327.

  113. De Lathauwer L., De Moor B., Vandewalle J., "A prewhitening-induced bound on the identification error in independent component analysis", IEEE Transactions on Circuits and Systems - I : Regular Papers, vol. 52, no. 3, Mar. 2005, pp. 546-554.

  114. De Lathauwer L., De Moor B., Vandewalle J., "Independent component analysis and (simultaneous) third-order tensor diagonalization", IEEE Transactions on Signal Processing, vol. 49, no. 10, Oct. 2001, pp. 2262-2271.

  115. De Lathauwer L., Comon P., "Editorial - Blind source separation and multichannel deconvolution", Signal Processing, Special Issue on Blind Source Separation and Multichannel Deconvolution, vol. 73, no. 1-2, Feb. 1999, pp. 1-2.

  116. De Lathauwer L., De Moor B., Vandewalle J., "Fetal Electrocardiogram Extraction by Blind Source Subspace Separation", IEEE Transactions on Biomedical Engineering, Special Topic Section on Advances in Statistical Signal Processing for Biomedicine, vol. 47, no. 5, May 2000, pp. 567-572.

  117. De Lathauwer L., De Moor B., Vandewalle J., "An Introduction to Independent Component Analysis", Journal of Chemometrics, Special Issue on Multi-Way Analysis, vol. 14, no. 3, May-Jun. 2000, pp. 123-149.

  118. Chu D., De Lathauwer L., De Moor B., "On the computation of the restricted singular value decomposition via the cosine-sine decomposition", SIAM Journal on Matrix Analysis and Applications, vol. 22, no. 2, 2000, pp. 580-601.

  119. Chu D., De Lathauwer L., De Moor B., "A QR-type reduction for computing the SVD of a general matrix product/quotient", Numerische Mathematik, vol. 95, no. 1, Jul. 2003, pp. 101-121.

  120. De Lathauwer L., De Moor B., Vandewalle J., "On the Best rank-1 and Rank-$(R_1, R_2, ..., R_N)$ Approximation and Applications of Higher-Order Tensors", SIAM J. Matrix Anal. Appl., vol. 21, no. 4, Apr. 2000, pp. 1324-1342.

  121. De Lathauwer L., De Moor B., Vandewalle J., "A multilinear singular value decomposition", SIAM J. Matrix Anal. Appl., vol. 21, no. 4, Apr. 2000, pp. 1253-1278.

National Journal Papers

  1. Van Gestel T., De Moor B., De Lathauwer L., Lemmerling P., Buijs J., Favoreel W., Vanderick L., Depreter A., Hoornaert L., Crepel M., "Survey of specific electric consumptions and consumption profiles of domestic appliances", Revue d'Electricit'e et d'Electronique Industrielle - Tijdschrift voor Elektriciteit en Industriële Electronica, Speical Issue on les émissions de CO2 due á la conversion d'énergie : une analyse du cycle de vie - De oorsprong van CO2-emissies ten gevolge van energieconversie, herfst 2000, pp. 14-19.

International Conference Papers

  1. Evert E., Vervliet N., Domanov I., De Lathauwer L., "Uniqueness result and algebraic algorithm for decomposition into multilinear rank-$ terms and joint block diagonalization", in 2023 IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) (CAMSAP), Los Suenos, Costa Rica, Dec. 2023, pp. 206-210.

  2. Widdershoven R., Govindarajan N., De Lathauwer L., "Overdetermined systems of polynomial equations: tensor-based solution and application", in Proc. of the 31st European Signal Processing Conference (EUSIPCO 2023), Helsinki, Finland, Sep. 2023, pp. 650-654.

  3. Hendrikx S., Sorensen M., De Lathauwer L., "Multilinear singular value decomposition of a tensor with fibers observed along one mode", in Proc. of the 22nd IEEE Statistical Signal Processing Workshop (SSP), Hanoi, Vietnam, Jul. 2023, pp. 566-570.

  4. Evert E., Vandecappelle M., De Lathauwer L., "CPD Computation via recursive eigenspace decompositions", in Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Singapore, Singapore, May 2022, pp. 9067-9071.

  5. Hautecoeur C., Glineur F., De Lathauwer L., "Hierarchical alternating nonlinear least squares for nonnegative matrix factorization using rational functions", in Proc. of the 29th European Signal Processing Conference (EUPISCO), Dublin, Ireland, Aug. 2021, pp. 1045-1049.

  6. Hendrikx S., Vervliet N., Bousse M., De Lathauwer L., "Thesis abstract: Tensor-based pattern recognition, data analysis and learning", in Proc. of BNAIC/BeneLearn 2020, Leiden, the Netherlands, Nov. 2020, pp. 416-417.

  7. Ayvaz M., De Lathauwer L., "Tensor-Based Multivariate Polynomial Optimization with Application in Blind Identification", in Proc. of the 29th European Signal Processing Conference (EUSIPCO), Dublin, Ireland, Aug. 2021, pp. 1080-1084.

  8. Vervliet N., Themelis A., Patrinos P., De Lathauwer L., "A quadratically convergent proximal algorithm for nonnegative tensor decomposition", in 2020 28th European Signal Processing Conference (EUSIPCO) (EUSIPCO), Amsterdam, The Netherlands, Jan. 2021, pp. 1020-1024.

  9. Vandecappelle M., De Lathauwer L., "Low Multilinear Rank Updating", in Proc. of the 53rd Asilomar Conference on Signals, Systems and Computers (ASILOMAR 2019), Pacific Grove, United States of America, Nov. 2019, pp. 437-441.

  10. Hendrikx S., Bousse M., Vervliet N., De Lathauwer L., "Algebraic and optimization based algorithms for multivariate regression using symmetric tensor decomposition", in Proc. of the 2019 IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Le Gosier, France, Dec. 2019, pp. 475-479.

  11. Chatzichristos C., Vandecappelle M., Kofidis E., Theodoridis S., De Lathauwer L., Van Huffel S., "Tensor-based Blind fMRI Source Separation Without the Gaussian Noise Assumption --- A beta-Divergence Approach", in Global Conference on Signal and Information Processing, Tensor Symposium (Globalsip), Ottawa, Canada, Nov. 2019.

  12. Goovaerts G., Padhy S., Bousse M., De Lathauwer L., Van Huffel S., "The power of tensor-based approaches in ECG signal processing", in Biomedical data fusion using tensors of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2019), Berlin, Germany, Jul. 2019.

  13. Vervliet N., Vandecappelle M., Bousse M., Zink R., De Lathauwer L., "Recent numerical and conceptual advances for tensor decompositions---A preview of Tensorlab 4.0", in Proc. of the 2019 IEEE Data Science Workshop (IEEE DSW), Minneapolis, United States of America, Jun. 2019, pp. 310-314.

  14. Caicedo A., De Wel O., Vandecappelle M., Thewissen L., Smits A., Allegaert K., De Lathauwer L., Naulaers G., Van Huffel S., "Monitoring of Brain Hemodynamics Coupling in Neonates using Updated Tensor Decompositions", in Proc. of the 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, Jul. 2019, pp. 660-663.

  15. Van Eyndhoven S., Vervliet N., De Lathauwer L., Van Huffel S., "Identifying Stable Components of Matrix/Tensor Factorizations via Low-Rank Approximation of Inter-Factorization Similarity", in Proc. of the 27th European Signal Processing Conference (EUSIPCO), A Coruna, Spain, Sep. 2019.

  16. Bousse M., Sidiropoulos N., De Lathauwer L., "NLS algorithm for Kronecker-structured linear systems with a CPD constrained solution", in Proc. of the 27th European Signal Processing Conference (EUSIPCO), A coruna, Spain, Sep. 2019, pp. 1-5.

  17. Vandecappelle M., Vervliet N., De Lathauwer L., "Rank-one Tensor Approximation with Beta-divergence Cost Functions", in Proc. of the 27th European Signal Processing Conference (EUSIPCO 2019), A Coruna, Spain, Sep. 2019, pp. 1319--1323.

  18. Sorensen M., Sidiropoulos N.D., De Lathauwer L., "Canonical polyadic decomposition of a tensor that has missing fibers: a monomial factorization approach", in International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, Jan. 2019, pp. 7490-7494.

  19. Van Eyndhoven S., Bousse M., Hunyadi B., De Lathauwer L., Van Huffel S., "Single-channel EEG classification by multi-channel tensor subspace learning and regression", in Proc. of the 28th IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2018), September, Aalborg, Denmark), pp. 1-6.

  20. Geirnaert S., Goovaerts G., Padhy S., Bousse M., De Lathauwer L., Van Huffel S., "Tensor-based ECG Signal Processing Applied to Atrial Fibrillation Detection", in Proc. of the 2018 52nd Asilomar Conference on Signals, Systems, and Computers (ACSSC), Pacific Grove, California, Oct. 2018, pp. 799-805.

  21. Bousse M., De Lathauwer L., "Large-Scale Autoregressive System Identification Using Kronecker Product Equations", in Proc. of the 2018 6th IEEE Global Conference on Signal and Information Processing (GlobalSIP), Anaheim, CA, Nov. 2018, pp. 1348--1352.

  22. Vandecappelle M., Bousse M., Vervliet N., Vendeville M., Zink R., De Lathauwer L., "Tensorlab 4.0 -- A preview", in Proc. of the 14th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2018), Guildford, United Kingdom, Jul. 2018, pp. 1--2.

  23. Olikier G., Absil P.-A., De Lathauwer L., "Variable projection applied to block term decomposition of higher-order tensors", in Proc. of the 14th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2018), Surrey, UK, Jul. 2018, pp. 139-148.

  24. De Lathauwer L., Kofidis E., "Coupled Matrix-Tensor Factorizations --- The Case of Partially Shared Factors", in Proc. of the 51st Asilomar Conference on Signals, Systems, and Computers (Asilomar 2018), Pacific Grove, California, Nov. 2018, pp. 711-715.

  25. Vandecappelle M., Bousse M., Vervliet N., De Lathauwer L., "CPD Updating Using Low-rank Weights", in Proceedings of the 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2018), Calgary, Canada, Apr. 2018, pp. 6368-6372.

  26. Bousse M., De Lathauwer L., "Nonlinear Least Squares Algorithm for Canonical Polyadic Decomposition Using Low-Rank Weights", in Proc. of the IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2017), Curaçao, Dutch Antilles, Dec. 2017, pp. 39-43.

  27. Vandecappelle M., Vervliet N., De Lathauwer L., "Nonlinear Least Squares Updating of the Canonical Polyadic Decomposition", in Proc. of the 25th European Signal Processing Conference (EUSIPCO17), Kos, Greece, Mar. 2017, pp. 693-697.

  28. Bousse M., Vervliet N., Debals O., De Lathauwer L., "Face Recognition as a Kronecker Product Equation", in Proc. of the IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2017), Curaçao, Dutch Antilles, Dec. 2017, pp. 276-280.

  29. Van Eyndhoven S., Hunyadi B., De Lathauwer L., Van Huffel S., "Flexible Fusion of Electroencephalography and Functional Magnetic Resonance Imaging: Revealing Neural-Hemodynamic Coupling Through Structured Matrix-Tensor Factorization", in Proc. of the 25th European Signal Processing Conference (EUSIPCO ), Kos, Greece, Aug. 2017, pp. 26-30.

  30. Bousse M., Goovaerts G., Vervliet N., Debals O., Van Huffel S., De Lathauwer L., "Irregular Heartbeat Classification Using Kronecker Product Equations", in Proc. of the 39th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC'17), Jeju Island, South Korea, Jul. 2017, pp. 438-441.

  31. Vervliet N., Debals O., De Lathauwer L., "Tensorlab 3.0 --- Numerical optimization strategies for large-scale constrained and coupled matrix/tensor factorization", in Proc. of the 50th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, Nov. 2016, pp. 1733--1738.

  32. Van Eeghem F., De Lathauwer L., "Second-order tensor-based convolutive ICA: deconvolution versus tensorization", in Proc. of the 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP2017), New Orleans, United States of America, Mar. 2017, pp. 2252-2256.

  33. Sorensen M., De Lathauwer L., "Shift Invariance, Incomplete Arrays and Coupled CPD: a Case Study", in Proc. of The Ninth IEEE Sensor Array and Multichannel Signal Processing Workshop, Rio de Janeiro, Brazil, Jul. 2016, 5 p.

  34. Bharath H.N., Sauwen N., Sima D.M., Himmelreich U., De Lathauwer L., Van Huffel S., "Canonical polyadic decomposition for tissue type differentiation using multi-parametric MRI in high-grade gliomas", in European Signal Processing Conference (EUSIPCO 2016), Budapest, Hungary, 5 p.

  35. Bousse M., Debals O., De Lathauwer L., "A Tensor-Based Method for Large-Scale Blind System Identification Using Segmentation", in Proc. of the 24th European Signal Processing Conference. (EUSIPCO 2016), Budapest, Hungary, Sep. 2016, pp. 2015-2019.

  36. Gong X., Lin Q., Debals O., Vervliet N., De Lathauwer L., "Coupled rank-$ block term decomposition by coupled block simultaneous generalized Schur decomposition", in 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP2016), Shanghai, China, Mar. 2016, pp. 2554-2558.

  37. Dreesen P., Goossens T., Ishteva M., De Lathauwer L., Schoukens J., "Block-Decoupling Multivariate Polynomials Using the Tensor Block-Term Decomposition", in Latent Variable Analysis and Signal Separation, (Vincent E., Yeredor A., Koldovsky Z., and Tichavsky P., eds.), Proc. of the 12th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2015), vol. 9237 of mph{Lecture Notes in Computer Science (LNCS)}, Springer International Publishing Switzerland, 2015, pp. 14--21.

  38. Bharath H.N., Sima D.M., Sauwen N., Himmelreich U., De Lathauwer L., Van Huffel S., "Tensor Based Tumor Tissue Type Differentiation Using Magnetic Resonance Spectroscopic Imaging", in Proc. of the Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE (EMBC), Milan, Italy, Aug. 2015, pp. 7003-7006.

  39. Markovsky I., Debals O., De Lathauwer L., "Sum-of-Exponentials Modeling and Common Dynamics Estimation Using Tensorlab", in Proc. of the 20th World Congress of the International Federation of Automatic Control (IFAC 2017), Toulouse, France, Jul. 2017, pp. 14715-14720.

  40. Debals O., De Lathauwer L., "Stochastic and Deterministic Tensorization for Blind Signal Separation", in Latent Variable Analysis and Signal Separation, (Vincent E., Yeredor A., Koldovsky Z., and Tichavsky P., eds.), 12th International Conference on Latent Variable Analysis and Signal Separation, vol. 9237 of mph{Lecture Notes in Computer Science}, Springer International Publishing, 2015, pp. 3--13.

  41. Bousse M., Debals O., De Lathauwer L., "A novel deterministic method for large-scale blind source separation", in Proc. of the 23rd European Signal Processing Conference (EUSIPCO), Nice, France, Sep. 2015, pp. 1935-1939.

  42. Debals O., Van Barel M., De Lathauwer L., "Blind Signal Separation of Rational Functions using Löwner-based Tensorization", in Proc. of the International Conference on Acoustics, Speech, Signal Processing (ICASSP), Brisbane, Australia, Apr. 2015, pp. 4145-4149.

  43. Sorensen M., De Lathauwer L., "Multidimensional ESPRIT: A Coupled Canonical Polyadic Decomposition Approach", in Proc. of the Eighth IEEE Sensor Array and Multichannel Signal Processing Workshop, A Coruna, Spain, Jun. 2014, 4 p.

  44. Sorensen M., De Lathauwer L., "Coupled Tensor Decompositions for Applications in Array Signal Processing", in Proc. of the 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) (CAMSAP 2013), Radisson Blu Resort, Saint Martin, Dec. 2013, 4 p.

  45. Sorensen M., De Lathauwer L., "Tensor Decompositions with Vandermonde Factor and Applications in Signal Processing", in Proc. of the Asilomar Conference on Signals, Systems, and Computers 2012 (Asilomar 2012), California, USA, Nov. 2012, 5 p.

  46. Sorensen M., De Lathauwer L., "Tensor Decompositions with Block-Toeplitz Structure and Applications in Signal Processing", in Proc. of the Asilomar Conference on Signals, Systems, and Computers (Asilomar 2011), Monterey, California, Nov. 2011, 5 p.

  47. De Lathauwer L., "Block Component Analysis, a New Concept for Blind Source Separation", in Proc. of the 10th International Conference on Latent Variable Analysis and Signal Separation (LVA ICA 2012), Tel-Aviv, Israel, Mar. 2012, pp. 1-8.

  48. De Lathauwer L., "A Short Introduction to Tensor-Based Methods for Factor Analysis and Blind Source Separation", in Proc. of the7th International Symposium on Image and Signal Processing and Analysis (ISPA 2011), Dubrovnik, Croatia, Sep. 2011, pp. 558-563.

  49. Sorensen M., De Lathauwer L., "New simultaneous generalized schur decomposition methods for the computation of the canonical polyadic decomposition", in Proc. of the Proc. of the Asilomar Conference on Signals, Systems, and Computers (Asilomar 2010), Monterey, USA, Nov. 2010, pp. 13-17.

  50. Domanov I., De Lathauwer L., "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.

  51. Signoretto M., De Lathauwer L., Suykens J.A.K., "Convex Multilinear Estimation and Operatorial Representations", in Proc. of the NIPS Workshop on Tensors, Kernels and Machine Learning 2010 (TKML), Whistler, Canada, Dec. 2010.

  52. Nion D., Vandewoestyne B., Vanaverbeke S., Van Den Abeele K., De Gersem H., De Lathauwer L., "A Time-Frequency Technique for Blind Separation and Localization of Pure Delayed Sources", in Proc. of the Ninth International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2010), St. Malo, France, Sep. 2010, pp. 546-554.

  53. Domanov I., De Lathauwer L., "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.

  54. Ishteva M., Absil P.A., Van Huffel S., De Lathauwer L., "Local minima of the best low multilinear rank approximation of tensors", in Proc. of the 19th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2010), Budapest, Hungary, Jul. 2010, pp. 2145-2146.

  55. Signoretto M., De Lathauwer L., Suykens J.A.K., "Kernel-based Learning from Infinite Dimensional 2-way Tensors", in ICANN 2010, part II, LNCS 6353, (Diamantaras K., Duch W., and Iliadis L.S. , eds.), Springer-Verlag, 2010, pp. 59-69.

  56. Signoretto M., Pelckmans K., De Lathauwer L., Suykens J.A.K., "Improved Non-Parametric Sparse Recovery with Data Matched Penalties", in 2nd International Workshop on Cognitive Information Processing (CIP), Elba Island, Italy, Apr. 2010, 6 p.

  57. Ishteva M., Absil P.-A., Van Huffel S., De Lathauwer L., "On the best low multilinear rank approximation of higher-order tensors", in Recent Advances in Optimization and its Applications in Engineering, (Diehl M., Glineur F., Jarlebring E., and Michiels W., eds.), Invited overview paper, Springer-Verlag, 2010, pp. 145-164.

  58. Liu X.H., De Lathauwer L., Janssens F., De Moor B., "Hybrid Clustering on Multiple Information Sources via HOSVD", in Proc. of the 7th International Symposium on Neural Networks (ISNN 2010), Shanghai, China, Jun. 2010, pp. 337-345.

  59. Sorensen M., De Lathauwer L., Deneire L., "PARAFAC with Orthogonality in One Mode and Applications in DS-CDMA Systems", in Proc. of the 2010 IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP 2010), Dallas, Texas, Mar. 2010, pp. 4142-4145.

  60. Nion D., De Lathauwer L., "A Link between the Decomposition of a Third-Order Tensor in Rank-(L,L,1) Terms and Joint Block Diagonalization", in Proc. of the IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP '09), Aruba, Dutch Antilles, Dec. 2009, pp. 89-92.

  61. Navasca C., De Lathauwer L., "Low Multilinear Rank Tensor Approximation via Semidefinite Programming", in Proc. of the 17th European Signal Processing Conference (EUSIPCO 2009), Glasgow, Scotland, Aug. 2009, pp. 520-524.

  62. Sorensen M., De Lathauwer L., Deneire L., "An Efficient Jacobi-Type Algorithm for Blind Equalization of Paraunitary Channels", in Proc. of the17th European Signal Processing Conference (EUSIPCO 2009), Glasgow, Scotland, Aug. 2009, pp. 510-514.

  63. Nion D., De Lathauwer L., "A Tensor-Based Blind DS-CDMA Receiver Using Simultaneous Matrix Diagonalization", in Proc. of the VIII IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2007), Helsinki, Finland, Jun. 2007, pp. CD-ROM.

  64. De Lathauwer L., "A Survey of Tensor Methods", in Proc. of the 2009 IEEE International Symposium on Circuits and Systems (ISCAS 2009), Taipei, Taiwan, May 2009, pp. 2773-2776.

  65. Karfoul A., Albera L., De Lathauwer L., "Canonical Decomposition of Even Higher Order Cumulant Arrays for Blind Underdetermined Mixture Identification", in Proc. of the Fifth IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2008), Darmstadt, Germany, Jul. 2008, pp. 501-505.

  66. Navasca C., De Lathauwer L., Kindermann S., "Swamp Reducing Technique for Tensor Decomposition", in Proc. of the16th European Signal Processing Conference (EUSIPCO 2008), Lausanne, Switzerland, Aug. 2008, 4 p.

  67. Ishteva M., De Lathauwer L., Absil P.-A., Van Huffel S., "The best rank-(R1,R2,R3) approximation of tensors by means of a geometric Newton method", in Proc. of the 6th International Conference of Numerical Analysis and Applied Mathematics (ICNAAM 2008), Kos, Greece, Sep. 2008, pp. 274-277.

  68. De Vos M., De Lathauwer L., Van Paesschen W., Van Huffel S., "Canonical Decomposition of scalp EEG in epileptic seizure localisation", in Proc. of the Asilomar conference on signals, systems and computers; invited paper (asilomar), Asilomar, California, Nov. 2007, pp. 403-407.

  69. Nion D., De Lathauwer L., "Block Receivers Based on Tensor Decompositions. Application in DS-CDMA and Over-sampled Systems.", in Proc. of the Asilomar Conference on Signals, Systems, and Computers (Asilomar 2007), Pacific Grove, California, Nov. 2007, pp. 403-407.

  70. De Vos M., De Lathauwer L., Van Huffel S., "Second order algorithm for imposing independence constraints to the CP model", in Proc. of the IEEE International Symposium on Circuits and Systems (ISCAS 08), Seattle, United States, May 2008, pp. 1344-1347.

  71. De Vos M., De Lathauwer L., Vanrumste B., Deburchgraeve W., Van Paesschen W and Van Huffel S., "Canonical Decomposition of scalp EEG as preprocessing for source localisation", in Proc. of the the 6th International Symposium on Noninvasive Functional Source Imaging of the Brain (nfsi 07), Hangzhou, China, Oct. 2007, pp. 377-400.

  72. De Vos M., De Lathauwer L., Van Huffel S., "Imposing independence constraints in the CP model", in Proc. of the 7th international conference on independent component analysis (ICA 07), London, England, Sep. 2007, pp. --.

  73. Ishteva M., De Lathauwer L., Van Huffel S., "Comparison of the performance of matrix and tensor based multi-channel harmonic analysis", in Proc. of the 7th International Conference on Mathematics in Signal Processing, Cirencester, UK, Dec. 2006, pp. 77-80.

  74. Nion D., De Lathauwer L., "A Block Factor Analysis Based Receiver for Blind Multi-user Access in Wireless Communications", in Proc. of the 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2006), Toulouse, France, May 2006, pp. 825-828.

  75. Nion D., De Lathauwer L., "Line Search Computation of the Block Factor Model for Blind Multi-user Access in Wireless Communications", in Proc. of the IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2006), Cannes, France, Jul. 2006, 5 p.

  76. Nion D., De Lathauwer L., "Levenberg-Marquardt Computation of the Block Factor Model for Blind Multi-user Access in Wireless Communications", in Proc. of the 14th European Signal Processing Conference (Eusipco 2006), Florence, Italy, Sep. 2006, pp. .

  77. De Vos M., De Lathauwer L., Vergult A. De Clercq W., Van Paesschen W., Van Huffel S., "Jacobi iterations for spatially constrained Independent Component Analysis", in Proc. of the 7th international conference on methematics in signal processing (IMA 2007), Cirencester, England, Dec. 2007, pp. 38-41.

  78. De Lathauwer L., Castaing J., "Second-Order Blind Identification of Underdetermined Mixtures", in Proc. of the 6th International Conference on Independent Component Analysis and Blind Source Separation (ICA 2006), Charleston, South Carolina, Mar. 2006, pp. 40-47.

  79. De Lathauwer L., "Parallel Factor Analysis by Means of Simultaneous Matrix Decompositions", in Proc. of the First IEEE Int. Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2005), Puerto Vallarta, Mexico, Dec. 2005, pp. 125-128.

  80. Laudadio T., Pels P., De Lathauwer L., Van Hecke P., Van Huffel S., "Unsupervised tissue segmentation of MRSI data using Canonical Correlation Analysis", in Proc. of the 2nd International Conference on Computational Intelligence in Medical and Healthcare (CIMED2005), Lisbon, Portugal, Jul. 2005, pp. 77-83.

  81. Boyer R., De Lathauwer L., Abed-Meraim K., "Delayed Exponential Fitting by Best Tensor Rank-$ Approximation", in Proceedings of the 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2005), Philadelphia, PA, Mar. 2005, pp. IV-269 -- IV-272.

  82. De Lathauwer L., Vandewalle J., "Dimensionality reduction in ICA and Rank-$ reduction in multilinear algebra", in Proc. of the Fifth International Conference on Independent Component Analysis and Blind Signal Separation (ICA 2004), Granada, Spain, Sep. 2004, pp. 295-302.

  83. Hoegaerts L., De Lathauwer L., Suykens J.A.K., Vandewalle J., "Efficiently updating and tracking the dominant Kernel Eigenspace", in Proc. of the the 16th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2004), Leuven, Belgium, Jul. 2004.

  84. Cruces S., Cichocki A., De Lathauwer L., "Thin QR and SVD factorizations for simultaneous blind signal extraction", in Proc. of the 12th European Signal Processing Conference (EUSIPCO 2004), Vienna, Austria, Sep. 2004, pp. 217-220.

  85. Castaing J., De Lathauwer L., "An algebraic technique for the blind separation of DS-CDMA signals", in Proc. of the 12th European Signal Processing Conference (EUSIPCO 2004), Vienna, Austria, Sep. 2004, pp. 377-380.

  86. De Lathauwer L., "Algebraic techniques for the blind deconvolution of constant modulus signals", in Proc. of the 12th European Signal Processing Conference (EUSIPCO 2004), Vienna, Austria, Sep. 2004, pp. 225-228.

  87. De Lathauwer L., Hoegaerts L., Vandewalle J., "A Grassmann-Rayleigh Quotient Iteration for Dimensionality Reduction in ICA", in Proc. of the Fifth International Conference on Independent Component Analysis and Blind Signal Separation (ICA 2004), Granada, Spain, Sep. 2004, pp. 335-342.

  88. Seghouane A.-K., De Lathauwer L., "A Bootstrap Model Selection Criterion Based on Kullback's Symmetric Divergence", in Proc. of the IEEE Workshop on Statistical Signal Processing (SSP'03), St. Louis, Missouri, Sep. 2003, 4 p.

  89. de Baynast A., Aazhang A., Declercq D., De Lathauwer L., "Bayesian blind parafac receivers for DS-CDMA systems", in Proc. of the IEEE workshop on statistical signal processing (SSP'03), St. Louis, Missouri, Sep. 2003, 4 p.

  90. de Baynast A., De Lathauwer L., Aazhang B., "Blind PARAFAC Receivers for Multiple Access - Multiple Antenna Systems", in Proc. of the IEEE Semiannual Vehicular Technology Conference (VTC'03), Orlando, FL, Oct. 2003, 5 p.

  91. Vandewalle J., De Lathauwer L., Comon P., "The generalized higher order singular value decomposition and the oriented signal-to-signal ratios of pairs of signal tensors and their use in signal processing", in Proc. of the European Conference on Circuit Theory and Design (ECCTD'03), Cracow, Poland, Sep. 2003, pp. I-389---I-392.

  92. De Lathauwer L., De Moor B., Vandewalle J., Cardoso J.-F, "Independent component analysis of largely underdetermined mixtures", in Proc. of the Fourth International Symposium on Independent Component Analysis and Blind Signal Separation (ICA 2003), Nara, Japan, Apr. 2003, pp. 29-34.

  93. De Lathauwer L., "The canonical decomposition and blind identification with more inputs than outputs : Some algebraic results", in Proc. of the Fourth International Symposium on Independent Component Analysis and Blind Signal Separation (ICA 2003), Nara, Japan, Apr. 2003, pp. 781-784.

  94. De Lathauwer L., "Simultaneous Matrix Diagonalization : the Overcomplete Case", in Proc. of the Fourth International Symposium on Independent Component Analysis and Blind Signal Separation (ICA 2003), Nara, Japan, Apr. 2003, pp. 821-825.

  95. Chen B., Petropulu A., De Lathauwer L., "Blind identification of complex convolutive MIMO systems with 3 sources and 2 sensors", in Proc. of the 2002 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2002), Orlando, Florida, May 2002, 4 p.

  96. Morren G., Wolf M., Lemmerling P., Wolf U., Choi J.H., Gratton E., De Lathauwer L., Van Huffel S., "Extraction of fast neuronal changes from multichannel, functional near infrared spectroscopy signals using independent component analysis", in Proceedings of SPIE; vol. 4623, Progress in Biomedical Optics and Imaging, vol. 3, no. 15 (SPIE-BiOS2002), San Jose, California, USA, Jan. 2002, pp. 68-76.

  97. De Lathauwer L., De Moor B., "On the blind separation of a class of non-circular complex sources.", in Proc. XIth European Signal Processing Conference (EUSIPCO-2002), Toulouse, France, Sep. 2002, 4 p.

  98. Chen B., Petropulu A., De Lathauwer L., "Blind Identification of Convolutive MIMO System with 3 sources and 2 sensors", in Proc. of the 2001 Conference on Information Science and Systems (CISS 2001), Baltimore, Maryland, Mar. 2001, pp. CD-ROM.

  99. De Lathauwer L., De Moor B., Vandewalle J., "An algebraic algorithm for ICA with more sources than sensors", in Mathematics in Signal Processing V, (McWhirter J., and Proudler I., eds.), Selected papers presented at 5th IMA int. Conf. on Mathematics in Signal Processing, Dec. 18-20, 2000, Univ. of Warwick, U.K., vol. V of Mathematics in Signal Processing, Clarendon Press (Oxford, UK), 2002, pp. 37-46.

  100. De Lathauwer L., De Moor B., Vandewalle J., "An Algebraic Approach to the Blind Identification of Paraunitary Filters", in CD-ROM Proc. of the IEEE Wireless Communications and Networking Conference 2000 (WCNC 2000), Chicago, USA, Sep. 2000, 4 p.

  101. Chen B., Petropulu A., De Lathauwer L., De Moor B., "Blind MIMO System Identification Based on Cross-Polyspectra", in Proc. of the Xth European Signal Processing Conference (EUSIPCO 2000), Tampere, Finland, Sept., 2000, pp. CD-ROM.

  102. De Lathauwer L., De Moor B., Vandewalle J., "An algebraic ICA algorithm for 3 sources and 2 sensors", in Proc. of the Xth European Signal Processing Conference (EUSIPCO 2000), Tampere, Finland, Sep. 2000, pp. CD-ROM.

  103. De Lathauwer L., De Moor B., Vandewalle J., "An algebraic approach to blind MIMO identification", in Proc. of the 2nd Int. Workshop on independent component analysis and blind source separation (ICA 2000), Helsinki, Finland, Jun. 2000, pp. 211-214.

  104. De Lathauwer L., De Moor B., Vandewalle J., "ICA techniques for more sources than sensors", in Proc. of the IEEE Signal Processing Workshop on Higher-Order Statistics (HOS'99), Caesarea, Israel, Jun. 1999, pp. 121-124.

  105. De Lathauwer L., Comon P., De Moor B., Vandewalle J., "ICA algorithms for 3 sources and 2 sensors", in Proc. of the IEEE Signal Processing Workshop on Higher-Order Statistics (HOS'99), Caesarea, Israel, Jun. 1999, pp. 116-120.

  106. De Lathauwer L., De Moor B., Vandewalle J., "SVD-based methodologies for fetal electrocardiogram extraction", in Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2000), Istanbul, Turkey, Jun. 2000, pp. 3771-3774.

  107. Cambre J., De Lathauwer L., De Moor B., "Best rank-(R,R,R) super-symmetric tensor approximation - a continuous-time approach", in Proc. IEEE Signal Processing Workshop on Higher-Order Statistics (HOS'99), Caesarea, Israel, Jun. 1999, pp. 242-246.

  108. De Lathauwer L., Vandewalle J., "A Residual Bound for the Mixing Matrix in ICA", in Proc. of the IXth European Signal Processing Conference (EUSIPCO-98), Rhodos, Greece, Sep. 1998, pp. 2065-2068.

  109. De Lathauwer L., De Moor B., Vandewalle J., "Dimensionality Reduction in Higher-Order-Only ICA", in Proc. of the IEEE Signal Processing Workshop on Higher-Order Statistics (HOS-97), Banff, Canada, Jul. 1997, pp. 316-320.

  110. De Lathauwer L., De Moor B., "From Matrix to Tensor : Multilinear Algebra and Signal Processing", in Mathematics in Signal Processing IV, (McWhirter J., ed.), Selected papers presented at 4th IMA Int. Conf. on Mathematics in Signal Processing, Oxford University Press (Oxford, United Kingdom), 1998, pp. 1-15.

  111. De Lathauwer L., De Moor B., "From matrix to tensor : multilinear algebra and signal processing", in Conf. Digest of the Fourth IMA International Conference on Mathematics in Signal Processing, Warwick, U.K, Dec. 1996, pp. 1-11.

  112. De Lathauwer L., De Moor B., Vandewalle J., "A technique for higher-order-only blind source separation", in Proc. of the International Conference on Neural Information Processing (ICONIP'96), Hong Kong, Sep. 1996, pp. 1223-1228.

  113. De Lathauwer L., De Moor B., Vandewalle J., "Independent component analysis based on higher-order statistics only", in Proc. of the 8th IEEE SP Workshop on Statistical Signal and Array Processing (SSAP'96), Corfu, Greece, Jun. 1996, pp. 356-359.

  114. De Lathauwer L., De Moor B., Vandewalle J., "Blind source separation by simultaneous third-order tensor diagonalization", in Proc. of the 8th European Signal Processing Conference (EUSIPCO'96), Trieste, Italy, Sep. 1996, pp. 2089-2092.

  115. De Lathauwer L., Comon P., De Moor B., Vandewalle J., "Higher-order power method - application in independent component analysis", in Proc. of the International Symposium on Nonlinear Theory and its Applications (NOLTA'95), Las Vegas, Nevada, Dec. 1995, pp. 91-96.

  116. De Lathauwer L., De Moor B., Vandewalle J., "Blind source separation by higher-order singular value decomposition", in Proc. of the 7th European Signal Processing Conference (EUSIPCO'94), Edinburgh, UK, Sep. 1994, pp. 175-178.

  117. De Lathauwer L., De Moor B., Vandewalle J., "The application of higher-order singular value decomposition to independent component analysis", in SVD and Signal Processing, III: Algorithms, Architectures and Applications, (Moonen M., and De Moor B., eds.), Elsevier, 1995, pp. 383-390.

  118. De Lathauwer L., De Moor B., Vandewalle J., "Canonical decomposition of a fourth-order tensor", in Book of abstracts of the Linear Algebra and Applications Conference, Manchester, U.K., Jul. 1995, 3 p.

  119. De Lathauwer L., De Moor B., Vandewalle J., "Fetal electrocardiogram extraction by independent component analysis", in Book of abstracts of the Linear Algebra and Applications Conference, Manchester, U.K., Jul. 1995, 3 p.

  120. De Lathauwer L., De Moor B., Vandewalle J., "Fetal electrocardiogram extraction by source subspace separation", in Proc. of IEEE Signal Processing / Athos Workshop on Higher-Order Statistics, Girona, Spain, Jun. 1995, pp. 134-138.

  121. De Lathauwer L., De Moor B., Vandewalle J., "A singular value decomposition for higher-order tensors", in Proc. of the ATHOS Workshop on System Identification and High-Order Statistics, Nice, France, Sep. 1993, 3 p.

National Conference Papers

  1. Albera L., Karfoul A., De Lathauwer L., "Decomposition Canonique de Tableaux Hermitiens Semi-definis Positifs d'Ordre Pair par Rotation Procusteenne: Application ݠ l'ICA", in Proc. of the 22ieme Colloque GRETSI sur le Traitement du Signal et des Images (GRETSI 2009), Dijon, France, Sep. 2009.

  2. Castaing J., De Lathauwer L., "Separation Aveugle de Signaux de Type DS-CDMA ݠl'Aide de Techniques Algޢriques", in Proc. of the 20ieme Colloque GRETSI sur le Traitement du Signal et des Images (GRETSI 2005), Louvain-la-Neuve, Belgium, Sep. 2005, 4 p.

  3. Nion D., De Lathauwer L., "Separation et Egalisation Aveugles de Signaux CDMA par la Dޣomposition en Blocs d'un Tenseur au Moyen de l'Algorithme de Levenberg-Marquardt", in Proc. of the 21ieme Colloque GRETSI sur le Traitement du Signal et des Images (GRETSI 2007), Troyes, France, Sep. 2007, pp. 245-248.

  4. De Vos M., De Lathauwer L., Vergult A., De Clercq W., Van Paesschen W., Van Huffel S., "Spatially Constrained Independent Component Analysis for real-time eye artifact removal from the electroencephalogram", in Proc. of the first Annual Symposium of the IEEE/EMBS Benelux Chapter. (IEEE EMBS), Brussel, Belgium, Dec. 2006, pp. 159-163.

  5. De Lathauwer L., Vandewalle J., De Moor B., "An algebraic Technique for blinf MIMO Deconvolution of Constant Modulus Signals", in Proc. of the 24th Symposium on Information Theory in the Benelux, Veldhoven, The Netherlands, May 2003, pp. 203-209.

  6. De Lathauwer L., de Baynast A., Vandewalle J., De Moor B., "New Algebraic Techniques for the Separation of DS-CDMA signals", in Proc. 24th Symposium on Information Theory in the Benelux, Veldhoven, The Netherlands, May 2003, pp. 211-218.

  7. De Lathauwer L., De Moor B., Vandewalle J., "An Algebraic Algorithm for Blind Identification with more Inputs than Outputs", in Proc. 23rd Symp. on Information Theory in the Benelux, Louvain-la-Neuve, Belgium, May 2002, pp. 241-246.

  8. De Lathauwer L., De Moor B., Vandewalle J., "An algorithm for joint diagnolization by a congruence transformation", in Proc. 23rd Symp. on Information Theory in the Benelux, Louvain-la-Neuve, Belgium, May 2002, pp. 235-240.

  9. De Lathauwer L., Fevotte C., De Moor B., Vandewalle J., "Jacobi Algorithm for Joint Block Diagonalization in Blind Idenfitication", in Proc. 23rd Symposium on Information Theory in the Benelux, Louvian-la-Neuve, Belgium, May 2002, pp. 155-162.

  10. de Baynast A., Fijalkow I., De Lathauwer L., "Egalisation aveugle multi-utilisateurs de Signaux DS-CDMA avec sequence d'embrouillage", in Proc. 18éme Colloque GRETSI sur le Traitement du Signal et des Images (GRETSI'01), Toulouse, France, Dept. 10-13, 2001, pp. 27-30.

  11. De Lathauwer L., Vandewalle J., De Moor B., "Jacobi-Algorithm for Simultaneous Generalized Schur Decomposition in Higher-Order-Only ICA", in Proc. of the IEEE Benelux Signal Processing Chapter 1998 Signal Processing Symposium (SPS'98), Leuven, Belgium, Mar. 1998, pp. 67-70.

  12. De Lathauwer L., De Moor B., Vandewalle J., "A singular value decomposition for higher-order tensors", in Proc. of the ProRISC/IEEE Workshop on Circuits, Systems and Signal-Processing, Houthalen, Belgium, Mar. 1993, pp. 37-43.

Ph.D.-theses

  1. De Lathauwer L., Signal Processing based on Multilinear Algebra, PhD thesis, Faculty of Engineering, KU Leuven (Leuven, Belgium), Sep. 1997, 256 p.

Internal Reports

  1. Widdershoven R., Vervliet N., De Lathauwer L., "A Bezoutian-Based Method for Solving Overdetermined Systems of Polynomial Equations", Internal Report 24-49, ESAT-SISTA, KU Leuven (Leuven, Belgium), 2024. Accepted for publication in 32nd European Signal Processing Conference, EUSIPCO 2024.

  2. Sofi S. S., Hendrikx S., De Lathauwer L., "Tensor train completion of multi-way data observed along one mode", Internal Report 24-34, ESAT-SISTA, KU Leuven (Leuven, Belgium), 2024. Accepted for publication in 32nd European Signal Processing Conference, EUSIPCO 2024.

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