Regularized least absolute deviations regression and an efficient algorithm for parameter tuning

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2006, Pages 690-700

  Wang, Li ^a   Gordon, Michael D ^a   Zhu, Ji ^b  

^a UNIVERSITY OF MICHIGAN   (United States)

^b UNIVERSITY OF MICHIGAN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

HEAVY-TAILED DISTRIBUTIONS; LEAST ABSOLUTE DEVIATION (LAD); OUTLIERS; SHRINKAGE METHODS;

COMPUTATIONAL METHODS; ERROR ANALYSIS; LINEAR REGRESSION; MATHEMATICAL MODELS; PARAMETER ESTIMATION; ROBUST CONTROL;

DATA REDUCTION;

EID: 84878078972     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2006.134     Document Type: Conference Paper

References (12)

1. M. Black and A. Rangarajan, "On the unification of line processes, outlier rejection, and robust statistics with applications in early vision," International Journal of Computer Vision, 25 (19):57-92, 1996
2. A. Giloni and M. Padberg, "Alternative methods of linear regression", Mathematical and Computer Modelling 35, 361-374, 2002
3. A. Giloni and M. Padberg, "The finite sample breakdown point of L1-regression," SIAM Journal on Optimization, 14, 1028-1042, 2004
4. A. Hamza and H. Krim, "Image denoising: A nonlinear robust statistical approach," IEEE Transaction on Signal Processing, 49 (12): 3045-3054, 2001
5. X. He, J. Jurechova, R. Koenker, and S. Portnoy, "Tail behavior of regression estimators and their breakdown points," Econometrica, 58, 1195-1214, 1990
6. S. Mika, B. Scholkopf, A. Smola, K. Muller, M. Scholz and G. Ratsch, "Kernel PCA and de-noising in feature spaces," Advances in Neural Information Processing Systems, vol 11, 537-542, MIT Press, 1999
7. I. Mizera and C.H. Muller, "The influence of the design on the breakdown points of L1-type M-esimators," Advances in Model-Oriented Design and Analysis, Physica-Verlag, Heidelberg, 193-200, 2001
8. T. Takahashi and T. Kurita, "Robust de-noising by kernel PCA," Artificial Neural Networks, 727-732, Springer Verlag, 2002
9. W.F. Sharpe, "Mean-absolute-deviation characteristic lines for securities and portfolios," Management Science 18, B1-B13, 1971
10. R. Tibshirani, "Regression shrinkage and selection via the lasso," Journal of Royal Statistical Society, Vol. 58, No.1, 267-288, 1996
11. K. Tsuda and G. Ratsch, "Image reconstruction by linear programming," Nerual Information Processing Systems (NIPS), 2003
12. M. Yuan, "GACV for quantile smoothing splines," Computational Statistics and Data Analysis, 2005