| Author | Title | Year | Journal/Proceedings | Reftype | DOI/URL |
|---|---|---|---|---|---|
| Basu, S., Banerjee, A. & Mooney, R.J. | Active Semi-Supervision for Pairwise Constrained Clustering | 2004 | Proceedings of the SIAM International Conference on Data Mining, pp. 333-344 | article | URL |
| Abstract: Semi-supervised clustering uses a small amount of supervised
ta to aid unsupervised learning. One typical approach ecifies a limited number of must-link and cannotlink nstraints between pairs of examples. This paper esents a pairwise constrained clustering framework and a w method for actively selecting informative pairwise constraints get improved clustering performance. The clustering d active learning methods are both easily scalable large datasets, and can handle very high dimensional data. perimental and theoretical results confirm that this active erying of pairwise constraints significantly improves the curacy of clustering when given a relatively small amount supervision. |
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BibTeX:
@article{Basu:EtAl:04,
author = {Basu, Sugato and Banerjee, Arindam and Mooney, Raymond J.},
title = {Active Semi-Supervision for Pairwise Constrained Clustering},
booktitle = {Proceedings of the SIAM International Conference on Data Mining},
year = {2004},
pages = {333--344},
url = {http://www.cs.utexas.edu/users/ml/papers/semi-sdm-04.pdf}
}
|
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| Bilenko, M., Basu, S. & Mooney, R.J. | Integrating constraints and metric learning in semi-supervised clustering. [BibTeX] |
2004 | ICML | inproceedings | URL |
BibTeX:
@inproceedings{conf/icml/BilenkoBM04,
author = {Bilenko, Mikhail and Basu, Sugato and Mooney, Raymond J.},
title = {Integrating constraints and metric learning in semi-supervised clustering.},
booktitle = {ICML},
year = {2004},
url = {http://www.cs.utexas.edu/users/ml/papers/semi-icml-04.pdf}
}
|
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