The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Csiszár’s Divergences for Non-negative Matrix Factorization: Family of New Algorithms
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Citations
Cites
Learning the parts of objects by non-negative matrix factorization
Lee, D. D., & Seung, H. S. (1999) · Nature · doi:10.1038/44565 · Cited by 13,868
Non-negative matrix factorization with sparseness constraints
Hoyer, P. O. (2004) · arXiv (Cornell University) · doi:10.48550/arxiv.cs/0408058 · Cited by 2,591
Differential-Geometrical Methods in Statistics
Amari, S.-I. (1985) · Lecture Notes in Statistics · doi:10.1007/978-1-4612-5056-2 · Cited by 1,673
Goodness-of-fit statistics for discrete multivariate data
(1989) · Choice Reviews Online · doi:10.5860/choice.26-2740 · Cited by 738
Information geometry of the EM and em algorithms for neural networks
Amari, S.-I. (1995) · Neural Networks · doi:10.1016/0893-6080(95)00003-8 · Cited by 331
Self-citationA Generalized Divergence Measure for Nonnegative Matrix Factorization
Kompass, R. (2007) · Neural Computation · doi:10.1162/neco.2007.19.3.780 · Cited by 191
Accelerating the EMML algorithm and related iterative algorithms by rescaled block-iterative methods
Byrne, C. L. (1998) · IEEE Transactions on Image Processing · doi:10.1109/83.650854 · Cited by 157
Recovery of constituent spectra using non-negative matrix factorization
Sajda, P., Du, S., & Parra, L. C. (2003) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.504676 · Cited by 94
Nonnegative features of spectro-temporal sounds for classification
Cho, Y.-C., & Choi, S. (2004) · Pattern Recognition Letters · doi:10.1016/j.patrec.2004.11.026 · Cited by 69
Cited by
Online Non-Negative Convolutive Pattern Learning for Speech Signals
Wang, D., Vipperla, R., Evans, N., & Zheng, T. F. (2013) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2012.2222381 · Cited by 25
Metadata
- Authors
- Cichocki, A., Zdunek, R., & Amari, S.-I.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2006
- Volume
- 3889
- Pages
- 32-39
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1547060653
- Cited by
- 271
- References
- 9
- FWCI
- 24.60
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Csiszár’s Divergences for Non-negative Matrix Factorization: Family of New Algorithms. https://app.cochat.ai/papers/10.1007/11679363_5
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- Cichocki, A., Zdunek, R., & Amari, S.-I. (2006). Csiszár’s Divergences for Non-negative Matrix Factorization: Family of New Algorithms. Lecture Notes in Computer Science. https://doi.org/10.1007/11679363_5
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
