Dirichlet aggregation: Unsupervised learning towards an optimal metric for proportional data

ACM International Conference Proceeding Series

Volumn 227, Issue , 2007, Pages 959-966

  Wang, Hua Yan ^a   Zha, Hongbin ^a   Qin, Hong ^b  

^a PEKING UNIVERSITY   (China)

^b USA

Author keywords

[No Author keywords available]

Indexed keywords

ABSTRACTING; AD HOC NETWORKS; CLASSIFICATION (OF INFORMATION); INFORMATION RETRIEVAL; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD; PARAMETERIZATION;

FRAMEWORK; OPTIMAL METRIC; SIMPLEX VERTEX AFFINITIES;

PROPORTIONAL CONTROL SYSTEMS;

EID: 34547993972     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1273496.1273617     Document Type: Conference Paper

References (25)

1. Blei, D. M., Ng, A. Y., Jordan, M. I. (2003) Latent Dirichlet Allocation. Journal of Machine Learning Research, 3(2003), 993-1022.
2. Blei, D. M. and Lafferty, J. D. (2006) Correlated Topic Models. In NIPS, volume 18.
3. Bouguila, N. and Ziou, D. (2006) Unsupervised Selection of a Finite Dirichlet Mixture Model: An MML-Based Approach. IEEE Transactions on Knowledge and Data Engineering. Vol.18, No.8.
4. Buntine, W. and Jakulin, A. (2004) Applying Discrete PCA in Data Analysis In Proceedings of the 20th UAI.
5. Csurka, G., Dance, C. R., Fan, L., Willamowski, J., Bray, C. (2004) Visual Categorization with Bags of Keypoints. In the 8th ECCV, Workshop on Statistical Learning in Computer Vision.
6. Deerwester, S., Dumais, S., Landauer, T., Furnas, G., Harshman, R. (1990) Indexing by Latent Semantic Analysis. Journal of the American Society of Information Science, 41(6), 391-407.
7. Gehler, P. V., Holub, A. D., Welling, M. (2006) The Rate Adapting Possion Model for Information Retrieval and Object Recognition. In Proceedings of the 23rd ICML.
8. Hofmann, T. (2001) Unsupervised Learning by Probabilistic Latent Semantic Analysis. Machine Learning, 42, 177-196.
9. Lebanon, G. (2003) Learning Riemannian Metrics. In Proceedings of the 19th UAI.
10. Fei-Fei, Fergus, R., Perona, P. (2004) Learning Generative Visual Models from Few Training Examples: an Incremental Bayesian Approach Tested on 101 Object Categories. IEEE. CVPR, Workshop on Generative-Model Based Vision.
11. Lowe, D. G. (2004) Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision, 60(2), 91-110.
12. Marlin, B. and Zemel, R. (2004) The Multiple Multiplicative Factor Model for Collaborative Filtering. In Proceedings of the 21st ICML.
13. Minka, T. P. (2003) Estimating a Dirichlet Distribution. Technical Report, Microsoft Research.
14. Omer, I. and Werman, M. (2006) Image Specific Feature Similarities. In Proceedings of the 9th ECCV.
15. Puzicha, J., Hofmann, T., Buhmann, J. (1997) Non-parametric Similarity Measures for Unsupervised Texture Segmentation and Image Retrieval. In Proceedings of the IEEE. CVPR, pp.267-272.
16. Roweis, S. and Saul, L. (2000) Nonlinear Dimensionality Reduction by Locally Linear Embedding. Science. 290: 2323-2326
17. Rubner, Y., Tomasi, C., Guibas, L. J. (2000) The Earth Mover's Distance as a Metric for Image Retrieval. International Journal of Computer Vision, 40(2), 99-121.
18. Salton, G. and McGill, M. editors (1983). Introduction to Modern Information Retrieval. McGraw-Hill.
19. Schütze, H. (1993) Word Space. In NIPS, volume 5.
20. Sjolander, K., Karplus, K., Brown, M., Hughey, R., Krogh, A., Mian, I.S., Haussler, D. (1996) Dirichlet Mixtures: A Method for Improving Detection of Weak but Significant Protein Sequence Homology. CABIOS, 12(4): 327-345
21. Swain, M. J. and Ballard, D. H. (1991) Color Indexing. International Journal of Computer Vision, 7(1), 11-32.
22. Tenenbaum, J., Silva, V.d., Langford, J. (2000) A Global Geometric Framework for Nonlinear Dimensionality Reduction. Science. 290: 2319-2323
23. Welling, M., Rosen-Zvi, M., Hinton, G. (2004) Exponential Family Harmoniums with an Application to Information Retrieval. In NIPS, volume 16.
24. Wyszecki, G. and Stiles, W. S. (1982) Color Science: Concepts and Methods, Quantitative Data and Formulae. John Wiley and Sons: New York, NY.
25. Yamamoto, M. and Sadamitsu, K. (2005) Dirichlet Mixtures in Text Modeling. Technical report. CS-TR-05-1. University of Tsukuba.