The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Multiple Incomplete Views Clustering via Weighted Nonnegative Matrix Factorization with $$L_{2,1}$$ Regularization
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Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
Advances in neural information processing systems 7
Cios, K., & Shields, M. (1997) · Neurocomputing · doi:10.1016/s0925-2312(97)90018-7 · Cited by 22,059
Advances in Neural Information Processing Systems 19
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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
Combining labeled and unlabeled data with co-training
Blum, A., & Mitchell, T. (1998) · Proceedings of the eleventh annual conference on Computational learning theory · doi:10.1145/279943.279962 · Cited by 5,495
Document clustering based on non-negative matrix factorization
Xu, W., Liu, X., & Gong, Y. (2003) · Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval · doi:10.1145/860435.860485 · Cited by 1,860
Argyriou, A., Evgeniou, T., & Pontil, M. (2007) · Advances in Neural Information Processing Systems 19 · doi:10.7551/mitpress/7503.003.0010 · Cited by 1,333
Orthogonal nonnegative matrix t-factorizations for clustering
Ding, C., Li, T., Peng, W., & Park, H. (2006) · Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/1150402.1150420 · Cited by 1,245
Co-regularized Multi-view Spectral Clustering
Kumar, A., Rai, P., & Daumé, H. (2011) · Cited by 1,093
Analyzing the effectiveness and applicability of co-training
Nigam, K., & Ghani, R. (2000) · Proceedings of the ninth international conference on Information and knowledge management · doi:10.1145/354756.354805 · Cited by 1,005
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Multi-view learning overview: Recent progress and new challenges
Zhao, J., Xie, X., Xu, X., & Sun, S. (2017) · Information Fusion · doi:10.1016/j.inffus.2017.02.007 · Cited by 1,002
Late Fusion Incomplete Multi-View Clustering
Liu, X., Zhu, X., Li, M., Wang, L., Tang, C., Yin, J., Shen, D., Wang, H., & Gao, W. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2879108 · Cited by 363
Multiple Kernel k-means with Incomplete Kernels
Liu, X., Gao, W., Zhu, X., Li, M., Wang, L., Zhu, E., Liu, T., Kloft, M., Shen, D., & Yin, J. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2892416 · Cited by 300
Integrative epigenetic taxonomy of primary prostate cancer
Stelloo, S., Nevedomskaya, E., Kim, Y., Schuurman, K., Valle-Encinas, E., Lobo, J., Krijgsman, O., Peeper, D. S., Chang, S. L., Feng, F. Y.-C., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-07270-2 · Cited by 154
Metadata
- Authors
- Shao, W., He, L., & Yu, P. S.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2015
- Pages
- 318-334
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1879834137
- Cited by
- 281
- References
- 36
- FWCI
- 6.25
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Multiple Incomplete Views Clustering via Weighted Nonnegative Matrix Factorization with $$L_{2,1}$$ Regularization. https://app.cochat.ai/papers/10.1007/978-3-319-23528-8_20
- The paper
- Shao, W., He, L., & Yu, P. S. (2015). Multiple Incomplete Views Clustering via Weighted Nonnegative Matrix Factorization with $$L_{2,1}$$ Regularization. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-319-23528-8_20
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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.
