期刊
SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS
卷 24, 期 3, 页码 762-767出版社
SIAM PUBLICATIONS
DOI: 10.1137/S0895479801394465
关键词
singular value decomposition; principal components analysis; multidimensional arrays; higher-order tensor; multilinear algebra
Earlier work has shown that no extension of the Eckart-Young SVD approximation theorem can be made to the strong orthogonal rank tensor decomposition. Here, we present a counterexample to the extension of the Eckart-Young SVD approximation theorem to the orthogonal rank tensor decomposition, answering an open question previously posed by Kolda [SIAM J. Matrix Anal. Appl., 23 (2001), pp. 243-355].
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