Weighted Low-Rank Approximations

Proceedings, Twentieth International Conference on Machine Learning

Volumn 2, Issue , 2003, Pages 720-727

  Srebro, Nathan ^a   Jaakkola, Tommi ^a  

^a USA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COLLABORATIVE FILTERING; GAUSSIAN NOISE; LOW-RANK APPROXIMATIONS; OPTIMAL SOLUTIONS;

APPROXIMATION THEORY; DIGITAL FILTERS; ERROR ANALYSIS; FUNCTIONS; MATRIX ALGEBRA; OPTIMIZATION; PROBABILITY; PROBLEM SOLVING; SAMPLING; VECTORS;

DATA PROCESSING;

EID: 1942516801     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. Azar, Y., Fiat, A., Karlin, A. R., McSherry, F., & Saia, J. (2001). Spectral analysis of data. Proceedings of the Thirty Third ACM Symposium on Theory of Computing.
2. Billsus, D., & Pazzani, M. J. (1998). Learning collaborative information filters. Proceedings of 15th International Conference on Machine Learning.
3. Collins, M., Dasgupta, S., & Schapire, R. (2002). A generalization of principal component analysis to the exponential family. Advances in Neural Information Processing Systems 14.
4. Goldberg, K., Roeder, T., Gupta, D., & Perkins, C. (2001). Eigentaste: A constant time collaborative filtering algorithm. Information Retrieval, 4, 133-151.
5. 2 models. Advances in Neural Information Processing Systems 15.
6. Irani, M., & Anandan, P. (2000). Factorization with uncertainty. Proceedings of the Sixth European Conference, on Computer Vision.
7. Jaakkola, T., & Jordan, M. (2000). Bayesian parameter estimation via variational methods. Statistics and Computing, 10, 25-37.
8. Lu, W.-S., Pel, S.-C., & Wang, P.-H. (1997). Weighted low-rank approximation of general complex matrices and its application in the design of 2-D digital filters. IEEE Transactions on Circuits and Systems - I, 44, 650-655.
9. Schein, A. I., Saul, L. K., & Ungar, L. H. (2003). A generalized linear model for principal component analysis of binary data. Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics.
10. Shpak, D. (1990). A weighted-least-squares matrix decomposition method with application to the design of two-dimensional digital filters. IEEE Thirty Third Midwest Symposium on Circuits and Systems.
11. Tenenbaum, J. B., & Freeman, W. T. (2000). Separating style and content with bilinear models. Neural Computation, 12, 1247-1283.
12. Young, G. (1940). Maximum likelihood estimation and factor analysis. Psychometrika, 6, 49-53.