PARAFAC algorithms for large-scale problems, Neurocomputing, vol.74, issue.11, pp.1970-1984, 2011. ,
DOI : 10.1016/j.neucom.2010.06.030
Large-scale matrix factorization with distributed stochastic gradient descent, Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '11, 2011. ,
DOI : 10.1145/2020408.2020426
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.230.7682
A comparison of algorithms for fitting the PARAFAC model, Computational Statistics & Data Analysis, vol.50, issue.7, pp.1700-1734, 2006. ,
DOI : 10.1016/j.csda.2004.11.013
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
Simultaneous search for all modes in multilinear models, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.4114-4117 ,
DOI : 10.1109/ICASSP.2010.5495727
Adaptive Algorithms to Track the PARAFAC Decomposition of a Third-Order Tensor, IEEE Transactions on Signal Processing, vol.57, issue.6, pp.2299-2310, 2009. ,
DOI : 10.1109/TSP.2009.2016885
Distributed parafac based DS-CDMA blind receiver for wireless sensor networks, 2010 IEEE 11th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2010. ,
DOI : 10.1109/SPAWC.2010.5671048
URL : https://hal.archives-ouvertes.fr/hal-00480584
Distributed Khatri-Rao space-time coding and decoding for cooperative networks, Proc. EUSIPCO 2011, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00598662
Distributed average consensus with least-mean-square deviation, Journal of Parallel and Distributed Computing, vol.67, issue.1, pp.33-46, 2007. ,
DOI : 10.1016/j.jpdc.2006.08.010
GigaTensor, Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '12, 2012. ,
DOI : 10.1145/2339530.2339583
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
Scalable tensor factorizations for incomplete data, Chemometrics and Intelligent Laboratory Systems, vol.106, issue.1, pp.41-56, 2011. ,
DOI : 10.1016/j.chemolab.2010.08.004
Multi-Way Compressed Sensing for Sparse Low-Rank Tensors, IEEE Signal Proc. Letters, pp.757-760, 2012. ,
DOI : 10.1109/LSP.2012.2210872
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.393.9339
Distributed computation of tensor decompositions in collaborative networks, 2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2013. ,
DOI : 10.1109/CAMSAP.2013.6714050
URL : https://hal.archives-ouvertes.fr/hal-00912384
Foundation of the PARAFAC procedure: models and conditions for an " explanatory " multimodal factor analysis, UCLA working papers in phonetics, vol.16, pp.1-84, 1970. ,
Analysis of individual differences in multidimensional scaling via an n-way generalization of ???Eckart-Young??? decomposition, Psychometrika, vol.12, issue.3, pp.283-319, 1970. ,
DOI : 10.1007/BF02310791
Community detection via heterogeneous interaction analysis, Data Mining and Knowledge Discovery, vol.3, issue.2, pp.1-33, 2012. ,
DOI : 10.1007/s10618-011-0231-0
Clustering With Multi-Layer Graphs: A Spectral Perspective, IEEE Transactions on Signal Processing, vol.60, issue.11, pp.5820-5831, 2012. ,
DOI : 10.1109/TSP.2012.2212886
Graph Laplacian based matrix design for finite-time distributed average consensus, 2012 American Control Conference (ACC), 2012. ,
DOI : 10.1109/ACC.2012.6315398
URL : https://hal.archives-ouvertes.fr/hal-00680344
Step-size sequence design for finite-time average consensus in secure wireless sensor networks, Systems & Control Letters, vol.67 ,
DOI : 10.1016/j.sysconle.2014.01.010
URL : https://hal.archives-ouvertes.fr/hal-00967327
Cramér-Rao lower bounds for low-rank decomposition of multidimensional arrays, IEEE Transactions on Signal Processing, vol.49, issue.9, pp.2074-2086, 2011. ,