Efficient Nonnegative Tucker Decompositions: Algorithms and Uniqueness.
IEEE Transactions on Image Processing(2015)
摘要
Nonnegative Tucker decomposition (NTD) is a powerful tool for the extraction of nonnegative parts-based and physically meaningful latent components from high-dimensional tensor data while preserving the natural multilinear structure of data. However, as the data tensor often has multiple modes and is large scale, the existing NTD algorithms suffer from a very high computational complexity in terms...
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关键词
Tensile stress,Matrix decomposition,Face,Sociology,Statistics,Approximation algorithms,Computational complexity
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