The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Convex and Semi-Nonnegative Matrix Factorizations
Abstract
We present several new variations on the theme of nonnegative matrix factorization (NMF). Considering factorizations of the form X=FG(T), we focus on algorithms in which G is restricted to containing nonnegative entries, but allowing the data matrix X to have mixed signs, thus extending the applicable range of NMF methods. We also consider algorithms in which the basis vectors of F are constrained to be convex combinations of the data points. This is used for a kernel extension of NMF. We provide algorithms for computing these new factorizations and we provide supporting theoretical analysis. We also analyze the relationships between our algorithms and clustering algorithms, and consider the implications for sparseness of solutions. Finally, we present experimental results that explore the properties of these new methods.
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ALGORITHMS FOR NON-NEGATIVE MATRIX FACTORIZATION
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Probabilistic Latent Semantic Indexing
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Cited by
Data-Driven Intelligent Transportation Systems: A Survey
Zhang, J., Wang, F.-Y., Wang, K., Lin, W.-H., Xu, X., & Chen, C. (2011) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2011.2158001 · Cited by 1,817
Joint Unsupervised Learning of Deep Representations and Image Clusters
Yang, J., Parikh, D., & Batra, D. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.556 · Cited by 879
Functional boundaries in the human cerebellum revealed by a multi-domain task battery
King, M., Hernandez-Castillo, C. R., Poldrack, R. A., Ivry, R. B., & Diedrichsen, J. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0436-x · Cited by 673
Kim, J., He, Y., & Park, H. (2014) · Journal of Global Optimization · doi:10.1007/s10898-013-0035-4 · Cited by 352
(2012) · Cited by 253
Metadata
- Authors
- Ding, C. H. Q., Li, T., & Jordan, M. I.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2010-01
- Volume
- 32
- Issue
- 1
- Pages
- 45-55
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2168103112
- Cited by
- 1,317
- References
- 41
- FWCI
- 47.73
- Type
- journal article
- Language
- en
- Open access
- closed
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- Ding, C. H. Q., Li, T., & Jordan, M. I. (2010). Convex and Semi-Nonnegative Matrix Factorizations. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/tpami.2008.277
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