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Grassmannian learning mutual subspace method for image set recognition
The image set is represented by a low-dimensional input subspace; and this input subspace is matched with reference subspaces by a similarity of their canonical angles, an interpretable and easy to compute metric.
Text Classification based on Word Subspace with Term-Frequency
To measure the similarity between texts, we propose the novel concept of word subspace, which can represent the intrinsic variability of features in a set of word vectors.
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