Higher-order principal component analysis for the approximation of tensors in tree-based low-rank formats
نویسندگان
چکیده
منابع مشابه
Sparse Principal Component Analysis via Regularized Low Rank Matrix Approximation
Principal component analysis (PCA) is a widely used tool for data analysis and dimension reduction in applications throughout science and engineering. However, the principal components (PCs) can sometimes be difficult to interpret, because they are linear combinations of all the original variables. To facilitate interpretation, sparse PCA produces modified PCs with sparse loadings, i.e. loading...
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ژورنال
عنوان ژورنال: Numerische Mathematik
سال: 2019
ISSN: 0029-599X,0945-3245
DOI: 10.1007/s00211-018-1017-8