R. A. Harshman, Foundations of the Parafac procedure, UCLA papers in phonetics, vol.16, pp.1-84, 1970.

A. Smilde, R. Bro, and P. Geladi, Multi-way analysis: applications in the chemical sciences, 2005.
DOI : 10.1002/0470012110

N. D. Sidiropoulos, G. B. Giannakis, and R. Bro, Blind PARAFAC receivers for DS-CDMA systems, IEEE Transactions on Signal Processing, vol.48, issue.3
DOI : 10.1109/78.824675

N. D. Sidiropoulos, R. Bro, and G. B. Giannakis, Parallel factor analysis in sensor array processing, IEEE Transactions on Signal Processing, vol.48, issue.8, pp.2377-2388, 2000.
DOI : 10.1109/78.852018

M. Mørup, Applications of tensor (multiway array) factorizations and decompositions in data mining, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, vol.61, issue.1, pp.24-40, 2011.
DOI : 10.1002/widm.1

P. Comon, X. Luciani, and A. L. De-almeida, Tensor decompositions, alternating least squares and other tales, Journal of Chemometrics, vol.78, issue.8, pp.393-405, 2009.
DOI : 10.1016/j.laa.2009.01.014/
URL : https://hal.archives-ouvertes.fr/hal-00410057

X. Liu and N. D. Sidiropoulos, Cramér-Rao lower bounds for low-rank decomposition of multidimensional arrays, IEEE Trans. Sig. Proc, vol.49, issue.9, pp.2074-2086, 2001.

S. F. Møller, J. Von-frese, and R. Bro, Robust methods for multivariate data analysis, Journal of Chemometrics, vol.75, issue.10, pp.549-563, 2005.
DOI : 10.1002/cem.962

S. Engelen and M. Hubert, Detecting outlying samples in a parallel factor analysis model, Analytica Chimica Acta, vol.705, issue.1-2, pp.155-165, 2011.
DOI : 10.1016/j.aca.2011.04.043

P. Paatero, Least squares formulation of robust non-negative factor analysis, Chemometrics and Intelligent Laboratory Systems, vol.37, issue.1, pp.23-35, 1997.
DOI : 10.1016/S0169-7439(96)00044-5

S. A. Vorobyov, Y. Rong, N. D. Sidiropoulos, and A. B. Gershman, Robust iterative fitting of multilinear models, IEEE Transactions on Signal Processing, vol.53, issue.8, pp.2678-2689, 2005.
DOI : 10.1109/TSP.2005.850343

M. Hubert, J. Van-kerckhoven, and T. Verdonck, Robust PARAFAC for incomplete data, Journal of Chemometrics, vol.58, issue.2, pp.290-298, 2012.
DOI : 10.1002/cem.2452

E. C. Chi and T. G. Kolda, Making tensor factorizations robust to non-Gaussian noise, 2010.
DOI : 10.2172/1011706

H. Kim, E. Ollila, V. Koivunen, and H. V. Poor, Robust iteratively reweighted Lasso for sparse tensor factorizations, 2014 IEEE Workshop on Statistical Signal Processing (SSP), pp.420-423, 2014.
DOI : 10.1109/SSP.2014.6884665

P. Comon, Tensors : A brief introduction, IEEE Signal Processing Magazine, vol.31, issue.3, pp.44-53, 2014.
DOI : 10.1109/MSP.2014.2298533
URL : https://hal.archives-ouvertes.fr/hal-00923279

E. H. Lloyd, Least-squares estimation of location and scale parameters using order statistics, Biometr, pp.88-95, 1952.

J. Jureckova, Nonparametric Estimate of Regression Coefficients, The Annals of Mathematical Statistics, vol.42, issue.4, pp.1328-1338, 1971.
DOI : 10.1214/aoms/1177693245

J. W. Mckean and R. M. Schrader, The geometry of robust procedures in linear models, Journal of the Royal Statistical Society. Series B, pp.366-371, 1980.

P. J. Rousseeuw and A. M. Leroy, Robust regression and outlier detection, 2005.
DOI : 10.1002/0471725382

J. D. Naranjo and J. W. Mckean, Rank regression with estimated scores, Statistics & Probability Letters, vol.33, issue.2, pp.209-216, 1997.
DOI : 10.1016/S0167-7152(97)00129-6

A. Swami, Cramer-Rao bounds for deterministic signals in additive and multiplicative noise, Signal Processing, vol.53, issue.2-3, pp.231-244, 1996.
DOI : 10.1016/0165-1684(96)00088-6