Tensor Factorization and Clustering for the Feature Extraction Based on Tucker3 with Updating Core
Aiming at the problems of Tucker3 to large-scale tensor when applied to feature extraction, a new factorization based on Tucker3 is proposed to extract feature from the tensors. First, the large-scale tensor is divided into multiple sub-tensors so as to conveniently compute cores of sub-tensors in parallel mode with Matlab Parallel Computing Toolbox; Then, the cores of each sub-tensor are updated for reducing deviation in calculating and the similar characteristics of sub-tensors are clustered to obtain the features. Experiment results show that this methods is able to extract features rapidly and efficiently.
H. J. Wang et al., "Tensor Factorization and Clustering for the Feature Extraction Based on Tucker3 with Updating Core", Advanced Materials Research, Vols. 308-310, pp. 2517-2522, 2011