Semi-supervised geodesic Generative Topographic Mapping

Pattern Recognition Letters

Volumn 31, Issue 3, 2010, Pages 202-209

  Cruz Barbosa, Raúl ^a,b   Vellido, Alfredo ^a  

^a UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

^b UNIVERSIDAD TECNOLÓGICA DE LA MIXTECA   (Mexico)

Author keywords

Generative Topographic Mapping; Geodesic distance; Label propagation; Semi supervised learning

Indexed keywords

CLASS LABELS; DATA MANIFOLDS; EUCLIDEAN DISTANCE; GENERATIVE TOPOGRAPHIC MAPPING; GEODESIC DISTANCES; LABEL PROPAGATION; LOW-DIMENSIONAL REPRESENTATION; MANIFOLD LEARNING; NEAREST NEIGHBOUR; NEIGHBOURHOOD; OBSERVED DATA; PROXIMITY GRAPHS; SEMI-SUPERVISED; SEMI-SUPERVISED LEARNING;

GEODESY; LABELS; SUPERVISED LEARNING;

MAPPING;

EID: 72449179321     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2009.09.029     Document Type: Article

References (21)

1. Archambeau C., and Verleysen M. Manifold constrained finite Gaussian mixtures. In: Cabestany J., Prieto A., and Sandoval D.F. (Eds). Proc. IWANN. LNCS vol. 3512 (2005), Springer-Verlag 820-828
2. Asuncion, A., Newman, D., 2007. UCI Machine Learning Repository. University of California, Irvine, School of Information and Computer Sciences. .
3. Belkin, M., Niyogi, P., 2002. Using manifold structure for partially labelled classification. Advances in Neural Information Processing Systems (NIPS). Vol. 15. MIT Press, pp. 929-936.
4. Belkin M., and Niyogi P. Semi-supervised learning on Riemannian manifolds. Machine Learning 56 (2004) 209-239
5. Bernstein, M., de Silva, V., Langford, J., Tenenbaum, J., 2000. Graph approximations to geodesics on embedded manifolds. Tech. rep., Stanford University, CA.
6. Bishop C.M., Svensén M., and Williams C.K.I. The Generative Topographic Mapping. Neural Comput. 10 1 (1998) 215-234
7. In: Chapelle O., Schölkopf B., and Zien A. (Eds). Semi-Supervised Learning (2006), The MIT Press
8. Cruz-Barbosa, R., Vellido, A., 2007. On the initialization of two-stage clustering with class-GTM. In: Borrajo, D., Castillo, L., Corchado, J. (Eds.), Proc. 12th Conf. of the Spanish Association for Artificial Intelligence, CAEPIA+TTIA 2007, LNAI, vol. 4788, pp. 50-59.
9. Cruz-Barbosa R., and Vellido A. On the improvement of the mapping trustworthiness and continuity of a manifold learning model. Proc. Ninth Internat. Conf. on Intelligent Data Engineering and Automated Learning (IDEAL 2008). LNCS vol. 5326 (2008), Springer 266-273
10. Cruz-Barbosa R., and Vellido A. Geodesic Generative Topographic Mapping. Proc. 11th Ibero-American Conf. on Artificial Intelligence (IBERAMIA 2008). LNAI vol. 5290 (2008), Springer 113-122
11. Cruz-Barbosa R., and Vellido A. Unfolding the manifold in Generative Topographic Mapping. Proc. Third Internat. Workshop on Hybrid Artificial Intelligence Systems (HAIS 2008). LNAI vol. 5271 (2008), Springer 392-399
12. Dijkstra E.W. A note on two problems in connection with graphs. Numer. Math. 1 (1959) 269-271
13. Herrmann, L., Ultsch, A., 2007. Label propagation for semi-supervised learning in self-organizing maps. In: Proc. Sixth WSOM 2007.
14. Jain A.K., and Dubes R.C. Algorithms for Clustering Data (1998), Prentice Hall, New Jersey
15. Lee J., and Verleysen M. Nonlinear Dimensionality Reduction (2007), Springer
16. Lee, J.A., Lendasse, A., Verleysen, M., 2002. Curvilinear distance analysis versus isomap. In: Proc. European Symposium on Artificial Neural Networks (ESANN), pp. 185-192.
17. Tenenbaum J.B., de Silva V., and Langford J.C. A global geometric framework for nonlinear dimensionality reduction. Science 290 (2000) 2319-2323
18. Ultsch, A., 2003. Maps for the visualization of high-dimensional data spaces. In: Proc. WSOM 2003, pp. 225-230.
19. Venna J., and Kaski S. Neighborhood preservation in nonlinear projection methods: An experimental study. In: Dorffner G., Bischof H., and Hornik K. (Eds). Proc. WSOM (2001), Springer 485-491
20. Wu, Z., Li, C.H., Zhu, J., Huang, J., 2006. A semi-supervised SVM for manifold learning. In: Proc. of the 18th International Conference on Pattern Recognition (ICPR'06), vol. 2, pp. 490-493.
21. Zhu, X., Ghahramani, Z., 2002. Learning from labeled and unlabeled data with label propagation. Tech. rep., CMU-CALD-02-107, Carnegie Mellon University.