L0-constrained regression for data mining

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4426 LNAI, Issue , 2007, Pages 981-988

  Wu, Zhili ^a   Li, Chun Hung ^a  

^a HONG KONG BAPTIST UNIVERSITY   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; CONSTRAINED OPTIMIZATION; ERROR ANALYSIS; FEATURE EXTRACTION; REGRESSION ANALYSIS;

CLASSIFIER CONSTRUCTION; CONSTRAINED REGRESSION; REGRESSION COEFFICIENTS;

DATA MINING;

EID: 38049175261     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-71701-0_110     Document Type: Conference Paper

References (8)

1. Tibshirani, R.: Regression shrinkage and selection via the lasso. In: Regression shrinkage and selection via the lasso. Technical report, University of Toronto, June 1994. (1994)
2. Hastie, T., Mallows, C.: A statistical view of some chemometrics regression tools (with discussion). Technometrics 35(2) (1993) 140-143
3. Bradley, P.S., Mangasarian, O.L.: Feature selection via concave minimization and support vector machines. In: Proc. 15th International Conf. on Machine Learning, Morgan Kaufmann, San Francisco, CA (1998) 82-90
4. Weston, J., Elisseeff, A., Scholkopf, B., Tipping, M.: The use of zero-norm with linear models and kernel methods. In: The use of zero-norm with linear models and kernel methods. JMLR, to appear. (2002)
5. Smola, A., Schoelkopf, B.: A tutorial on support vector regression. In: A tutorial on support vector regression, NeuroCOLT2 Technical Report NC2-TR-1998-030, 1998. (1998)
6. Fung, G.: The disputed federalist papers: Svm feature selection via concave minimization. In: TAPIA '03: Proceedings of the 2003 conference on Diversity in computing, New York, NY, USA, ACM Press (2003) 42-46
7. Smola, A., Scholkopf, B., Ratsch, G.: Linear programs for automatic accuracy control in regression. In: In Proceedings ICANN'99, Int. Conf. on Artificial Neural Networks, Berlin, 1999. Springer. (1999)
8. Weston, J., Gammerman, A., Stitson, M., Vapnik, V., Vovk, V., Watkins, C.: Support vector density estimation. In: Advances in Kernel Methods -Support Vector Learning, pages 293-306, Cambridge, MA, 1999. MIT Press. (1999)