SETRED: Self-training with editing

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3518 LNAI, Issue , 2005, Pages 611-621

  Li, Ming ^a   Zhou, Zhi Hua ^a  

^a NANJING UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

DATA PROCESSING; FILE EDITORS; ITERATIVE METHODS; MATHEMATICAL TECHNIQUES; PERSONNEL TRAINING;

DATA EDITING; LEARNED HYPOTHESIS; SELF TRAINING; SETRED;

LEARNING ALGORITHMS;

EID: 26944471649     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11430919_71     Document Type: Conference Paper

References (17)

1. Blum, A., Mitchell, T.: Combining labeled and unlabeled data with co-training. In: Proceedings of the 11th Annual. Conference on Computational Learning Theory, New York, NY (1998), 92-100
2. Cohen, I., Cozman, F.G., Sebe, N., Cirelo, M.C., Huang, T.S.: Semisupervised learning of classifier: theory, algorithms, and their application to human-computer interaction. IEEE Transactions on Pattern Analysis and Machine Intelligence 26 (2004) 1553-1567
3. Jiang, Y., Zhou, Z.-H.: Editing training data for kNN classifiers with neural network ensemble. In: Yin, F., Wang, J., Guo, C. (eds.): Lecture Notes in Computer Science, Vol.3173. Springer, Berlin (2004) 356-361
4. Joachims, T.: Transductive inference for text classification using support vector machines. In: Proceedings of the 16th International Conference on Machine Learning, San Francisco, CA (1999) 200-209
5. Lewis, D., Gale, W.: A sequential algorithm for training text classifiers. In: Proceedings of the 17th AOM International Conference on Research and Development in Information Retrieval, Dublin, Ireland (1994) 3-12
6. McCallum, A., Nigam, K.: Employing. EM in pool-based active learning for text classification. In: Proceedings of the 15th International Conference on Machine Learning, Madison, WI (1998) 359-367
7. Muhlenbach, F., Lallich, S., Zighed, D.A.: Identifying and handling mislabelled instances. Journal of Intelligent Information Systems 39 (2004) 89-109
8. Muslea, I., Minton, S., Knoblock, C.A.: Selective sampling with redundant views. In: Proceeding of the 17th International Conference on Machine Learning, Stanford, CA (2000) 621-626
9. Muslea, I., Minton, S., Knoblock, C.A.: Active + semi-supervised learning = robust multi-view learning. In: Proceeding of the 19th International Conference on Machine Learning, Sydney, Australia (2002) 435-442
10. Nigam, K., Ghani, R.: Analyzing the effectiveness and applicability of co-training. In: Proceedings of the 9th International Conference on Information and Knowledge Management, Washington, DC (2000) 86-93
11. Nigam, K., McCallum, A., Thrun, S., Mitchell, T.: Text classification from labeled and unlabeled documents using EM. Machine Learning 39 (2000) 103-134
12. Sarkar, A.: Applying co-training methods to statistical parsing. In: Proceedings of the 2nd Annual Meeting of the North American Chapter of the Association of Computational Linguistics. Pittsburgh. PA (2001) 95-102
13. Seeger, M.: Learning with labeled and unlabeled data. Technical Report, University of Edinburgh, Edinburgh, UK (2001)
14. Seuong, H., Opper, M., Sompolinski, H.: Query by committee. In: Proceedings of the 5th ACM Workshop on Computational Learning Theory, Pittsburgh, PA (1992) 287-294
15. Wilson, D.R.: Asymptotic properties of nearest neighbor rules using edited data. IEEE Transactions on Systems, Man and Cybernetics, 2 (1972) 408-421
16. Zhou, Z.-H., Chen, K.-J., Jiang, Y.: Exploiting unlabeled data in content-based image retrieval. In: Boulicaut, J.-F., Esposito, F., Giannotti, F., Pedreschi, D. (eds.): Lecture Notes in Artificial Intelligence, Vol.3201. Springer, Berlin (2004) 525-536
17. Zighed, D.A., Lallich, S., Muhlenbach, F.: Separability index in supervised learning. In: Elomaa, T., Mannila, H., Toivonen, H. (eds.) Lecture Notes in Artificial Intelligence, Vol.2431. Springer, Berlin (2002) 475-487