Multilinear Subspace Learning (MSL) dimensionality reduction of multidimensional data gives a comprehensive introduction to both theoretical and practical aspects of MSL for the dimensionality reduction of multidimensional data based on tensors. It covers the fundamentals, algorithms, and applications of MSL. It is an approach to dimensionality reduction. Dimensionality reduction can be performed on data tensor whose observations have been vectorized and organized into a data tensor, or whose observations are matrices that are concatenated into a data tensor.
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