Fast nonnegative matrix factorization and its application for protein fold recognition

Eurasip Journal on Applied Signal Processing

Volumn 2006, Issue , 2006, Pages

  Okun, Oleg ^a   Priisalu, Helen ^a  

^a UNIVERSITY OF OULU   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CONSTRAINT THEORY; ITERATIVE METHODS; MAPPING; MOLECULAR STRUCTURE; PARAMETER ESTIMATION;

CONVERGENCE; FAST NONNEGATIVE MATRIX FACTORIZATION; FEATURE SCALING; PROTEIN FOLD RECOGNIZATION;

PROTEINS;

EID: 33646424384     PISSN: 11108657     EISSN: 16870433     Source Type: Journal    
DOI: 10.1155/ASP/2006/71817     Document Type: Article

References (42)

1. I. T. Jolliffe, Principal Component Analysis, Springer, New York, NY, USA, 1986.
2. P. Common, "Independent component analysis," in Proceedings of the International Signal Processing Workshop on Higher-Order Statistics, pp. 111-120, Chamrousse, France, July 1991.
3. D. D. Lee and H. S. Seung, "Learning the parts of objects by non-negative matrix factorization," Nature, vol. 401, no. 6755, pp. 788-791, 1999.
4. S. Tsuge, M. Shishibori, S. Kuroiwa, and K. Kita, "Dimensionality reduction using non-negative matrix factorization for information retrieval," in Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, vol. 2, pp. 960-965, Tucson, Ariz, USA, July-October 2001.
5. B. Xu, J. Lu, and G. Huang, "A constrained non-negative matrix factorization in information retrieval," in Proceedings of the IEEE International Conference on Information Reuse and Integration (IRI '03), pp. 273-277, Las Vegas, Nev, USA, October 2003.
6. I. Buciu and I. Pitas, "Application of non-negative and local non negative matrix factorization to facial expression recognition," in Proceedings of the 17th International Conference on Pattern Recognition (ICPR '04), vol. 1, pp. 288-291, Cambridge, UK, 2004.
7. X. Chen, L. Gu, S. Z. Li, and H.-J. Zhang, "Learning representative local features for face detection," in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '01), vol. 1, pp. I-1126-I-1131, Kauai, Hawaii, USA, December 2001.
8. T. Feng, S. Z. Li, H.-Y. Shum, and H.-Y. Zhang, "Local non-negative matrix factorization as a visual representation," in Proceedings of the 2nd International Conference on Development and Learning, pp. 178-183, Cambridge, Mass, USA, June 2002.
9. D. Guillamet and J. Vitria, "Discriminant basis for object classification," in Proceedings of the 11th International Conference on Image Analysis and Processing, pp. 256-261, Palermo, Italy, September 2001.
10. D. Guillamet and J. Vitrià, "Evaluation of distance metrics for recognition based on non-negative matrix factorization," Pattern Recognition Letters, vol. 24, no. 9-10, pp. 1599-1605, 2003.
11. D. Guillamet, J. Vitrià, and B. Schiele, "Introducing a weighted non-negative matrix factorization for image classification," Pattern Recognition Letters, vol. 24, no. 14, pp. 2447-2454, 2003.
12. M. Rajapakse and L. Wyse, "NMF vs ICA for face recognition," in Proceedings of the 3rd International Symposium on Image and Signal Processing and Analysis (ISPA '03), vol. 2, pp. 605-610, Rome, Italy, September 2003.
13. R. Ramanath, W. E. Snyder, and H. Qi, "Eigenviews for object recognition in multispectral imaging systems," in Proceedings of the 32nd Applied Imagery Pattern Recognition Workshop, pp. 33-38, Washington, DC, USA, October 2003.
14. L. K. Saul and D. D. Lee, "Multiplicative updates for classification by mixture models," in Advances in Neural and Information Processing Systems, T. G. Dietterich, S. Becker, and Z. Ghahramani, Eds., vol. 14, pp. 897-904, MIT Press, Cambridge, Mass, USA, 2002.
15. Y. Wang, Y. Jia, C. Hu, and M. Turk, "Fisher non-negative matrix factorization for learning local features," in Proceedings of the 6th Asian Conference on Computer Vision, Jeju Island, Korea, January 2004.
16. P. O. Hoyer, "Non-negative matrix factorization with sparseness constraints," Journal of Machine Learning Research, vol. 5, pp. 1457-1469, 2004.
17. [17[ Y. Li and A. Cichocki, "Sparse representation of images using alternating linear programming," in Proceedings of the 7th International Symposium on Signal Processing and Its Applications (ISSPA '03), vol. 1, pp. 57-60, Paris, France, July 2003.
18. W. Liu, N. Zheng, and X. Lu, "Non-negative matrix factorization for visual coding," in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '03), vol. 3, pp. 293-296, Hong Kong, April 2003.
19. S. Behnke, "Discovering hierarchical speech features using convolutional non-negative matrix factorization," in Proceedings of the International Joint Conference on Neural Networks, vol. 4, pp. 2758-2763, Portland, Ore, USA, July 2003.
20. Y.-C. Cho, S. Choi, and S.-Y. Bang, "Non-negative component parts of sound for classification," in Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology (ISSPIT '03), pp. 633-636, Darmstadt, Germany, December 2003.
21. M. Novak and R. Mammone, "Use of non-negative matrix factorization for language model adaptation in a lecture transcription task," in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '01), vol. 1, pp. 541-544, Salt Lake City, Utah, USA, May 2001.
22. P. Smaragdis and J. C. Brown, "Non-negative matrix factorization for polyphonic music transcription," in Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, pp. 177-180, New Paltz, NY, USA, October 2003.
23. J. Lu, B. Xu, and H. Yang, "Matrix dimensionality reduction for mining Web logs," in Proceedings of the IEEE/WIC International Conference on Web Intelligence, pp. 405-408, Halifax, NS, Canada, October 2003.
24. Y. Mao and L. K. Saul, "Modeling distances in large-scale networks by matrix factorization," in Proceedings of the ACM Internet Measurement Conference, pp. 278-287, Sicily, Italy, October 2004.
25. M. Cooper and J. Foote, "Summarizing video using non-negative similarity matrix factorization," in Proceedings of the IEEE Workshop on Multimedia Signal Processing, pp. 25-28, St.Thomas, Virgin Islands, USA, December 2002.
26. J. Lawrence, S. Rusinkiewicz, and R. Ramamoorthi, "Efficient BRDF importance sampling using a factored representation," ACM Transactions on Graphics, vol. 23, no. 3, pp. 496-505, 2004. Special issue: Proceedings of the 2004 SIGGRAPH Conference.
27. M. D. Plumbley and E. Oja, "A "nonnegative PCA" algorithm for independent component analysis," IEEE Transactions on Neural Networks, vol. 15, no. 1, pp. 66-76, 2004.
28. G. Bologna and R. D. Appel, "A comparaison study on protein fold recognition," in Proceedings of the 9th International Conference on Neural Information Processing (ICONIP '02), vol. 5, pp. 2492-2496, Singapore, November 2002.
29. I.-F. Chung, C.-D. Huang, Y.-H. Shen, and C.-T. Lin, "Recognition of structure classification of protein folding by NN and SVM hierarchical learning architecture," in Artificial Neural Networks and Neural Information Processing (ICANN/ICONIP '03), O. Kaynak, E. Alpaydin, E. Oja, and L. Xu, Eds., vol. 2714 of Lecture Notes in Computer Science, pp. 1159-1167, Istanbul, Turkey, June 2003.
30. N. R. Pal and D. Chakraborty, "Some new features for protein fold recognition," in Artificial Neural Networks and Neural Information Processing (ICANN/ICONIP '03), O. Kaynak, E. Alpaydin, E. Oja, and L. Xu, Eds., vol. 2714 of Lecture Notes in Computer Science, pp. 1176-1183, Istanbul, Turkey, June 2003.
31. C. H.Q. Ding and I. Dubchak, "Multi-class protein fold recognition using support vector machines and neural networks," Bioinformatics, vol. 17, no. 4, pp. 349-358, 2001.
32. O. Okun, "Protein fold recognition with k-local hyperplane distance nearest neighbor algorithm," in Proceedings of the 2nd European Workshop on Data Mining and Text Mining for Bioinformatics, pp. 47-53, Pisa, Italy, September 2004.
33. L. Lo Conte, B. Ailey, T. J. P. Hubbard, S. E. Brenner, A. G. Murzin, and C. Chothia, "SCOP: a structural classification of proteins database," Nucleic Acids Research, vol. 28, no. 1, pp. 257-259, 2000.
34. C.-D. Huang, I.-F. Chung, N. R. Pal, and C.-T. Lin, "Machine learning for multi-class protein fold classification based on neural networks with feature gating," in Artificial Neural Networks and Neural Information Processing (ICANN/ICONIP '03), O. Kaynak, E. Alpaydin, E. Oja, and L. Xu, Eds., vol. 2714 of Lecture Notes in Computer Science, pp. 1168-1175, Istanbul, Turkey, June 2003.
35. O. Okun, "Feature normalization and selection for protein fold recognition," in Proceedings of the 11th Finnish Artificial Intelligence Conference, pp. 207-221, Vantaa, Finland, September 2004.
36. T. Cover and P. Hart, "Nearest neighbor pattern classification, " IEEE Transactions on Information Theory, vol. 13, no. 1, pp. 21-27, 1967.
37. K. Yu, L. Ji, and X. Zhang, "Kernel nearest-neighbor algorithm," Neural Processing Letters, vol. 15, no. 2, pp. 147-156, 2002.
38. P. Vincet and Y. Bengio, "K-local hyperlane and convex distance nearest neighbor algorithms," in Advances in Neural Information Processing Systems, T. G. Dietterich, S. Becker, and Z. Ghahramani, Eds., vol. 14, pp. 985-992, MIT Press, Cambridge, Mass, USA, 2002.
39. O. Okun, "K-local hyperplane distance nearest neighbor algorithm and protein fold recognition," Pattern Recognition and Image Analysis, vol. 16, no. 1, pp. 19-22, 2006.
40. O. Okun, "Non-negative matrix factorization and classifiers: experimental study," in Proceedings of the 4th IASTED International Conference on Visualization, Imaging, and Image Processing (VHP '04), pp. 550-555, Marbella, Spain, September 2004.
41. D. D. Lee and H. S. Seung, "Algorithms for non-negative matrix factorization," in Advances in Neural and Information Processing Systems, T. K. Leen, T. G. Dietterich, and V. Tresp, Eds., vol. 13, pp. 556-562, MIT Press, Cambridge, Mass, USA, 2001.
42. S. Kullback and R. A. Leibler, "On information and sufficiency," The Annals of Mathematical Statistics, vol. 22, no. 1, pp. 79-86, 1951.