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Sparse Alignment for Robust Tensor Learning
By: Lai, Z.; Sun, M.; Zhao, C.; Xu, Y.; Wong, W.K.;
2014 / IEEE
This item from - IEEE Transaction - Computing and Processing - Multilinear/tensor extensions of manifold learning based algorithms have been widely used in computer vision and pattern recognition. This paper first provides a systematic analysis of the multilinear extensions for the most popular methods by using alignment techniques, thereby obtaining a general tensor alignment framework. From this framework, it is easy to show that the manifold learning based tensor learning methods are intrinsically different from the alignment techniques. Based on the alignment framework, a robust tensor learning method called sparse tensor alignment (STA) is then proposed for unsupervised tensor feature extraction. Different from the existing tensor learning methods,
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