QUIC-SVD: Fast SVD using cosine trees

Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference

Volumn , Issue , 2009, Pages 673-680

  Holmes, Michael P ^a   Gray, Alexander G ^a   Lee Isbell, Charles ^a  

^a Georgia Institute of Technology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FORESTRY; LEARNING SYSTEMS; TREES (MATHEMATICS);

COMPUTATIONAL COSTS; EMPIRICAL TEST; FAST APPROXIMATION; KEY OPERATIONS; LARGE DATASETS; MACHINE LEARNING METHODS; MATRIX; ORDERS OF MAGNITUDE; REAL- TIME; SAMPLING MECHANISMS;

SINGULAR VALUE DECOMPOSITION;

EID: 84858783218     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

1. S. Friedland, A. Niknejad, M. Kaveh, and H. Zare. Fast Monte-Carlo Low Rank Approximations for Matrices. In Proceedings of Int. Conf. on System of Systems Engineering, 2006.
2. A. Deshpande and S. Vempala. Adaptive Sampling and Fast Low-Rank Matrix Approximation. In 10th International Workshop on Randomization and Computation (RANDOM06), 2006.
3. A. M. Frieze, R. Kannan, and S. Vempala. Fast Monte-Carlo Algorithms for Finding Low-Rank Approximations. In IEEE Symposium on Foundations of Computer Science, pages 370-378, 1998.
4. P. Drineas, R. Kannan, and M. W. Mahoney. Fast Monte Carlo Algorithms for Matrices II: Computing a Low-Rank Approximation to a Matrix. SIAM Journal on Computing, 36(1):158-183, 2006. (Pubitemid 46374022)
5. P. Drineas, E. Drinea, and P. S. Huggins. An Experimental Evaluation of a Monte-Carlo Algorithm for Singular Value Decomposition. Lectures Notes in Computer Science, 2563:279-296, 2003.
6. T. Sarlos. Improved Approximation Algorithms for Large Matrices via Random Projections. In 47th IEEE Symposium on Foundations of Computer Science (FOCS), pages 143-152, 2006. (Pubitemid 351175504)
7. D. Achlioptas, F. McSherry, and B. Scholkopf. Sampling Techniques for Kernel Methods. In Advances in Neural Information Processing Systems (NIPS) 17, 2002.
8. M. P. Holmes, A. G. Gray, and C. L.Isbell, Jr. Ultrafast Monte Carlo for Kernel Estimators and Generalized Statistical Summations. In Advances in Neural Information Processing Systems (NIPS) 21, 2008.
9. J. Audibert, R. Munos, and C. Szepesvari. Variance estimates and exploration function in multi-armed bandits. Technical report, CERTIS, 2007.