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First results on uniqueness of sparse non-negative matrix factorization

Theis, Fabian J., Stadlthanner, K. and Tanaka, T. (2005) First results on uniqueness of sparse non-negative matrix factorization. In: 13. European Signal Processing Conference, EUSIPCO 2005; 4 - 8 September 2005, Antalya, Turkey; proceedings; conference CD.

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Sparse non-negative matrix factorization (sNMF) allows for the decomposition of a given data set into a mixing matrix and a feature data set, which are both non-negative and fulfill certain sparsity conditions. In this paper it is shown that the employed projection step proposed by Hoyer has a unique solution, and that it indeed finds this solution. Then indeterminacies of the sNMF model are identified and first uniqueness results are presented, both theoretically and experimentally.

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Item type:Book section
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
Dewey Decimal Classification:500 Science > 570 Life sciences
Created at the University of Regensburg:Unknown
Item ID:17325
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