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Correlated Noise: How it Breaks NMF, and What to Do About It
Non-negative matrix factorization (NMF) is a problem of decomposing multivariate data into a set of features and their corresponding activations. When applied to experimental data, NMF has to cope with noise, which is often highly correlated. We show that correlated noise can break the Donoho and St...
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| Main Authors: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2010
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3673742/ https://ncbi.nlm.nih.gov/pubmed/23750288 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s11265-010-0511-8 |
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