Sample selection bias correction theory

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

Volumn 5254 LNAI, Issue , 2008, Pages 38-53

  Cortes, Corinna ^a   Mohri, Mehryar ^a,b   Riley, Michael ^a   Rostamizadeh, Afshin ^b  

^a GOOGLE INC   (United States)

^b NEW YORK UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA SETS; ESTIMATION TECHNIQUES; FINITE SAMPLES; MACHINE LEARNINGS; NOVEL CONCEPTS; SAMPLE BIASES; SAMPLE SELECTION BIASES; STABLE ALGORITHMS; THEORETICAL ANALYSES; WEIGHTING TECHNIQUES;

COMPUTATIONAL GRAMMARS; EDUCATION; ELECTRIC NETWORK ANALYSIS; ERROR CORRECTION; LEARNING SYSTEMS; WIRELESS TELECOMMUNICATION SYSTEMS;

LEARNING ALGORITHMS;

EID: 56749103116     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-87987-9_8     Document Type: Conference Paper

References (19)

1. Bickel, S., Brückner, M., Scheffer, T.: Discriminative learning for differing training and test distributions. In: ICML 2007, pp. 81-88 (2007)
2. Bousquet, O., Elisseeff, A.: Stability and generalization. JMLR 2, 499-526 (2002)
3. Breiman, L., Friedman, J., Olshen, R., Stone, C.: Classification and regression trees. CRC Press, Boca Raton (1984)
4. Cortes, C., Vapnik, V.N.: Support-Vector Networks. Machine Learning 20, 273-297 (1995)
5. Devroye, L., Wagner, T.: Distribution-free performance bounds for potential function rules. IEEE Trans. on Information Theory, 601-604 (1979)
6. Dudik, M., Schapire, R.E., Phillips, S.J.: Correcting sample selection bias in maximum entropy density estimation. In: NIPS 2005 (2006)
7. Elkan, C.: The foundations of cost-sensitive learning. In: IJCAI, pp. 973-978 (2001)
8. Fan, W., Davidson, I., Zadrozny, B., Yu, P.S.: An improved categorization of classifier's sensitivity on sample selection bias. In: ICDM 2005, pp. 605-608. IEEE Computer Society, Los Alamkos (2005)
9. Heckman, J.J.: Sample Selection Bias as a Specification Error. Econometrica 47, 151-161 (1979)
10. Huang, J., Smola, A., Gretton, A., Borgwardt, K., Schölkopf, B.: Correcting Sample Selection Bias by Unlabeled Data. Technical Report CS-2006-44). University of Waterloo (2006a)
11. Huang, J., Smola, A.J., Gretton, A., Borgwardt, K.M., Schölkopf, B.: Correcting sample selection bias by unlabeled data. In: NIPS 2006, pp. 601-608 (2006b)
12. Kearns, M., Ron, D.: Algorithmic stability and sanity-check bounds for leave-one-out cross-validation. In: COLT 1997, pp. 152-162 (1997)
13. Little, R.J.A., Rubin, D.B.: Statistical analysis with missing data. John Wiley & Sons, Inc., New York (1986)
14. Saunders, C., Gammerman, A., Vovk, V.: Ridge Regression Learning Algorithm in Dual Variables. In: ICML 1998, pp. 515-521 (1998)
15. Steinwart, I.: On the influence of the kernel on the consistency of support vector machines. JMLR 2, 67-93 (2002)
16. Sugiyama, M., Nakajima, S., Kashima, H., von Bünau, P., Kawanabe, M.: Direct importance estimation with model selection and its application to covariate shift adaptation. In: NIPS 2008 (2008)
17. Vapnik, V.N.: Statistical learning theory. Wiley-Interscience, New York (1998)
18. Zadrozny, B.: Learning and evaluating classifiers under sample selection bias. In: ICML 2004 (2004)
19. Zadrozny, B., Langford, J., Abe, N.: Cost-sensitive learning by cost-proportionate example weighting. In: ICDM 2003 (2003)