Sparse data embedding and prediction by tropical matrix factorization

Background: Matrix factorization methods are linear models, with limited capability to model complex relations. In our work, we use tropical semiring to introduce non-linearity into matrix factorization models. We propose a method called Sparse Tropical Matrix Factorization (STMF) for the estimation...

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Bibliographic Details
Main Authors:	Curk, T. (Author), Kazan, H. (Author), Oblak, P. (Author), Omanović, A. (Author)
Format:	Article
Language:	English
Published:	BioMed Central Ltd 2021
Subjects:	algorithm Algorithms article Biological data Data embedding embedding Expression measurements Factorization gene expression Gene expression Gene Expression Gene expression datasets genetics human Humans mathematics Matrix algebra Matrix completion Matrix factorization Matrix factorizations Model complexes neoplasm Neoplasms nonlinear system non-negative matrix factorization Nonnegative matrix factorization normal distribution Normal distribution prediction Sparse data Synthetic data Tropical factorization Tropical semiring Tropics
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Sparse data embedding and prediction by tropical matrix factorization

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