Sparse regression as a sparse Eigenvalue problem

2008 Information Theory and Applications Workshop - Conference Proceedings, ITA

Volumn , Issue , 2008, Pages 121-127

  Moghaddam, Baback ^a   Gruber, Amit ^b   Weiss, Yair ^b   Avidan, Shai ^c  

^a CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

^b HEBREW UNIVERSITY OF JERUSALEM   (Israel)

^c ADOBE RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EIGEN VALUE PROBLEMS; SPARSE REGRESSION;

CYBERNETICS; EIGENVALUES AND EIGENFUNCTIONS; FOOD PROCESSING;

INFORMATION THEORY;

EID: 52949092413     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ITA.2008.4601036     Document Type: Conference Paper

References (13)

1. S. Chen, D. L. Donoho, and M. A. Saunders. Atomic Decomposition by Basis Pursuit. SIAM Journal on Scientific Computing, 20(1):33-61, 1999.
2. A. d'Aspremont, L. El Ghaoui, M. I. Jordan, and G. R. G. Lanckriet. A Direct. Formulation for Sparse PCA using Semidefinite Programming. In Neural Information Processing Systems 17, 2004.
3. B. Efron, T. Hastie, I. Johnstone, and R. Tibshirani. Least Angle Regression. Annals of Statistics, 32(2):407-499, 2004.
4. G.H. Golub and C.F. Van Loan. Matrix Computations. Johns Hopkins Press, 1989.
5. B. Moghaddam, Y. Weiss, and S. Avidan. Generalized Spectral Bounds for Sparse LDA. In International Conference on Machine Learning. ICML'06, June 2006.
6. B. Moghaddam, Y. Weiss, and S. Avidan. Spectral Bounds for Sparse PCA: Exact & Greedy Algorithms. In Neural Information Processing Systems 18, 2006.
7. B. Moghaddam, Y. Weiss, and S. Avidan. Fast Pixel/Part. Selection with Sparse Eigenvectors. In International Conference on Computer Vision. ICCV'07, Rio de Janeiro, Brazil, October 2007.
8. P. B. Nair, A. Choudhury, and A. J. Keane. Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels. Journal of Machine Learning Research, 3:781-801, 2002.
9. B. K. Natarajan. Sparse Approximate Solutions to Linear Systems. SIAM Journal of Computing, 25(2):227-234, 1995.
10. G. L. Nemhauser and L. A. Wolsey. Integer and Combinatorial Optimization. John Wiley, New York, 1988.
11. C. E. Rasmussen and C. K. I. Williams. http://guassianprocesses.org/gpml/ code.
12. K. Sjöstrand. Matlab implementation of LASSO, LARS, the Elastic Net and SPCA. Informatics and Mathematical Modelling, Technical University of Denmark (DTU), 2005.
13. H. Zou, T. Hastie, and R. Tibshirani. Sparse Principal Component Analysis. Journal of Computational and Graphical Statistics, 15(2), 2003.