E. Papalexakis, K. Pelechrinis, and C. Faloutsos, “Spotting misbehaviors in location-based social networks using tensors,” in Proceedings of the 23rd International Conference on World Wide Web. ACM, 2014, pp. 551-552. [OpenAIRE]
 L. Yao, Q. Z. Sheng, Y. Qin, X. Wang, A. Shemshadi, and Q. He, “Context-aware point-of-interest recommendation using tensor factorization with social regularization,” in Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2015, pp. 1007-1010.
 X. Guo and Y. Ma, “Generalized tensor total variation minimization for visual data recovery?” in Proc. IEEE Conf. Comp. Vis. Patt. Recogn. IEEE, 2015, pp. 3603-3611.
 J. Liu, P. Musialski, P. Wonka, and J. Ye, “Tensor completion for estimating missing values in visual data,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 35, no. 1, pp. 208-220, 2013.
 Y.-L. Chen, C.-T. Hsu, and H.-Y. M. Liao, “Simultaneous tensor decomposition and completion using factor priors,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 36, no. 3, pp. 577-591, 2014.
 Q. Zhao, L. Zhang, and A. Cichocki, “Bayesian cp factorization of incomplete tensors with automatic rank determination,” PAMI, vol. 37, no. 9, pp. 1751-1763, 2015.
 B. W. Bader, T. G. Kolda et al., “Matlab tensor toolbox version 2.6,” Available online, February 2015. [Online]. Available: http://www.sandia.gov/ tgkolda/TensorToolbox/
 Q. Gu, H. Gui, and J. Han, “Robust tensor decomposition with gross corruption,” in Proc. Advances in Neural Inf. Process. Syst., 2014, pp. 1422-1430.
 Z. Zhang, G. Ely, S. Aeron, N. Hao, and M. Kilmer, “Novel methods for multilinear data completion and de-noising based on tensor-svd,” in Proc. IEEE Conf. Comp. Vis. Patt. Recogn., 2014, pp. 3842-3849.
 Q. Zhao, D. Meng, X. Kong, Q. Xie, W. Cao, Y. Wang, and Z. Xu, “A novel sparsity measure for tensor recovery,” in Proc. IEEE Int. Conf. Comp. Vis., 2015, pp. 271-279.
 Q. Zhao, G. Zhou, L. Zhang, A. Cichocki, and S.-I. Amari, “Bayesian robust tensor factorization for incomplete multiway data,” IEEE Trans. Neural Netw. & Learn. Syst., vol. 27, no. 4, pp. 736-748, 2016.
 D. Goldfarb and Z. Qin, “Robust low-rank tensor recovery: Models and algorithms,” SIAM Journal on Matrix Analysis and Applications, vol. 35, no. 1, pp. 225-253, 2014.
 Y. Xu, R. Hao, W. Yin, and Z. Su, “Parallel matrix factorization for low-rank tensor completion,” arXiv preprint arXiv:1312.1254, 2013.
 Z. Xu, F. Yan, and A. Qi, “Infinite tucker decomposition: Nonparametric bayesian models for multiway data analysis,” in Proc. Int. Conf. Mach. Learn., 2012, pp. 1023-1030.
 X. Chen, Z. Han, Y. Wang, Q. Zhao, D. Meng, and Y. Tang, “Robust tensor factorization with unknown noise,” in Proc. IEEE Conf. Comp. Vis. Patt. Recogn., 2016, pp. 5213-5221.