Tensor Factorization and Clustering for the Feature Extraction Based on Tucker3 with Updating Core

Abstract:

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.

• Periodical: Advanced Materials Research (Volumes 308-310)
• Pages: 2517-2522
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.308-310.2517
• Online since: August 2011
• Authors: Hai Jun Wang, Fei Yun Xu, Fei Wang
• Keywords: ALS Algorithm, Feature Extraction, Parallel Mode, Sub-Tensor, Tucker3, Update Core

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