T. G. Kolda and B. Bader, The TOPHITS model for higher-order web link analysis, Proceedings of Link Analysis, Counterterrorism and Security, 2006.

A. Carlson, J. Betteridge, B. Kisiel, B. Settles, E. R. Jr et al., Toward an architecture for never-ending language learning, AAAI, p.3, 2010.

K. Bollacker, C. Evans, P. Paritosh, T. Sturge, and J. Taylor, Freebase, Proceedings of the 2008 ACM SIGMOD international conference on Management of data , SIGMOD '08, pp.1247-1250, 2008.
DOI : 10.1145/1376616.1376746

S. Rendle, B. M. Leandro, A. Nanopoulos, and L. Schmidt-thieme, Learning optimal ranking with tensor factorization for tag recommendation, Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '09, pp.727-736, 2009.
DOI : 10.1145/1557019.1557100

P. Symeonidis, A. Nanopoulos, and Y. Manolopoulos, Tag recommendations based on tensor dimensionality reduction, Proceedings of the 2008 ACM conference on Recommender systems, RecSys '08, pp.43-50, 2008.
DOI : 10.1145/1454008.1454017

Y. Xu, L. Zhang, and W. Liu, Cubic Analysis of Social Bookmarking for Personalized Recommendation, Frontiers of WWW Research and Development-APWeb, pp.733-738, 2006.
DOI : 10.1007/11610113_66

C. J. Appellof and E. R. Davidson, Strategies for analyzing data from video fluorometric monitoring of liquid chromatographic effluents, Analytical Chemistry, vol.53, issue.13, pp.2053-2056, 1981.
DOI : 10.1021/ac00236a025

L. D. Lathauwer and B. D. Moor, From matrix to tensor: Multilinear algebra and signal processing, Institute of Mathematics and Its Applications Conference Series, pp.1-16, 1998.

M. A. Vasilescu and D. Terzopoulos, Multilinear analysis of image ensembles: TensorFaces, " in Computer Vision?ECCV, pp.447-460, 2002.

K. Maruhashi, F. Guo, and C. Faloutsos, MultiAspectForensics: Pattern Mining on Large-Scale Heterogeneous Networks with Tensor Analysis, 2011 International Conference on Advances in Social Networks Analysis and Mining, pp.203-210, 2011.
DOI : 10.1109/ASONAM.2011.80

W. Austin, G. Ballard, and T. G. Kolda, Parallel Tensor Compression for Large-Scale Scientific Data, 2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2015.
DOI : 10.1109/IPDPS.2016.67

I. Jeon, E. E. Papalexakis, U. Kang, and C. Faloutsos, HaTen2: Billion-scale tensor decompositions, 2015 IEEE 31st International Conference on Data Engineering, pp.1047-1058, 2015.
DOI : 10.1109/ICDE.2015.7113355

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

T. G. Kolda and B. Bader, Tensor Decompositions and Applications, SIAM Review, vol.51, issue.3, pp.455-500, 2009.
DOI : 10.1137/07070111X

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.130.782

L. D. Lathauwer, B. D. Moor, and J. Vandewalle, ) Approximation of Higher-Order Tensors, SIAM Journal on Matrix Analysis and Applications, vol.21, issue.4, pp.1324-1342, 2000.
DOI : 10.1137/S0895479898346995

O. Kaya and B. Uçar, Scalable sparse tensor decompositions in distributed memory systems, Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on, SC '15, pp.771-7711, 2015.
DOI : 10.1145/2807591.2807624

URL : https://hal.archives-ouvertes.fr/hal-01148202

J. E. Roman, C. Campos, E. Romero, A. Tomas, L. D. Lathauwer et al., SLEPc users manual A multilinear singular value decomposition, Sistemes Informàtics i Computació, Universitat Politècnica deVaì encia, pp.1253-1278, 2000.

T. G. Kolda and J. Sun, Scalable Tensor Decompositions for Multi-aspect Data Mining, 2008 Eighth IEEE International Conference on Data Mining, pp.363-372, 2008.
DOI : 10.1109/ICDM.2008.89

J. Li, C. Battaglino, I. Perros, J. Sun, and R. Vuduc, An inputadaptive and in-place approach to dense tensor-times-matrix multiply, Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, pp.761-7612, 2015.

K. Kaya, F. H. Rouet, and B. Uçar, On Partitioning Problems with Complex Objectives, Euro-Par 2011: Parallel Processing Workshops, pp.334-344
DOI : 10.1007/978-3-642-29737-3_38

URL : https://hal.archives-ouvertes.fr/hal-00763548

A. Pinar and B. Hendrickson, Partitioning for complex objectives, Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001
DOI : 10.1109/IPDPS.2001.925098

C. A. Andersson and R. Bro, The N-way Toolbox for MATLAB, Chemometrics and Intelligent Laboratory Systems, vol.52, issue.1, pp.1-4, 2000.
DOI : 10.1016/S0169-7439(00)00071-X

B. W. Bader and T. G. Kolda, Efficient MATLAB Computations with Sparse and Factored Tensors, SIAM Journal on Scientific Computing, vol.30, issue.1, pp.205-231, 2007.
DOI : 10.1137/060676489

M. Baskaran, B. Meister, N. Vasilache, and R. Lethin, Efficient and scalable computations with sparse tensors, 2012 IEEE Conference on High Performance Extreme Computing, pp.1-6, 2012.
DOI : 10.1109/HPEC.2012.6408676

M. M. Baskaran, B. Meister, and R. Lethin, Low-overhead loadbalanced scheduling for sparse tensor computations, IEEE Conference on High Performance Extreme Computing (HPEC), pp.1-6, 2014.

S. Smith, N. D. Ravindran, G. Sidiropoulos, and . Karypis, SPLATT: Efficient and Parallel Sparse Tensor-Matrix Multiplication, 2015 IEEE International Parallel and Distributed Processing Symposium, pp.61-70, 2015.
DOI : 10.1109/IPDPS.2015.27

U. Kang, E. Papalexakis, A. Harpale, and C. Faloutsos, GigaTensor, Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '12, pp.316-324, 2012.
DOI : 10.1145/2339530.2339583

J. H. Choi and S. V. Vishwanathan, DFacTo: Distributed factorization of tensors, 27th Advances in Neural Information Processing Systems, pp.1296-1304, 2014.

S. Smith and G. Karypis, DMS: Distributed sparse tensor factorization with alternating least squares, Tech. Rep, pp.15-22, 2015.

J. Bennett and S. Lanning, The netflix prize, Proceedings of KDD cup and workshop, p.35, 2007.

O. Görlitz, S. Sizov, S. Staab, ¨. U. , and C. Aykanat, PINTS: Peer-to-peer infrastructure for tagging systems, Proceedings of the 7th International Conference on Peer-to-Peer Systems, pp.19-36, 1999.

H. A. Kiers and A. Der-kinderen, A fast method for choosing the numbers of components in Tucker3 analysis, British Journal of Mathematical and Statistical Psychology, vol.56, issue.1, pp.119-125, 2003.
DOI : 10.1348/000711003321645386

O. Kaya and B. Uçar, High-performance parallel algorithms for the Tucker decomposition of higher order sparse tensors, Inria, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01219316

L. Eldén and B. Savas, A Newton???Grassmann Method for Computing the Best Multilinear Rank-$(r_1,$ $r_2,$ $r_3)$ Approximation of a Tensor, SIAM Journal on Matrix Analysis and Applications, vol.31, issue.2, pp.248-271, 2009.
DOI : 10.1137/070688316