Large Margin Component Analysis

NIPS 2006: Proceedings of the 19th International Conference on Neural Information Processing Systems

Volumn , Issue , 2006, Pages 1385-1392

  Torresani, Lorenzo ^a   Lee, Kuang Chih ^a  

^a Riya Inc   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING ALGORITHMS; NEAREST NEIGHBOR SEARCH; SUPPORT VECTOR MACHINES;

COMPONENT ANALYSIS; DIMENSIONALITY REDUCTION METHOD; DISTANCE-LEARNING; FEATURE DISTANCE; K-NEAREST NEIGHBOR CLASSIFICATION; LARGE MARGINS; LEARN+; LOW-DIMENSIONAL SUBSPACE; METRIC LEARNING; OVERFITTING;

DISTANCE EDUCATION;

EID: 85076906101     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

1. S. Chopra, R. Hadsell, and Y. LeCun. Learning a similarity metric discriminatively, with application to face verification. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, 2005.
2. R. A. Fisher. The use of multiple measurements in taxonomic problems. Ann. Eugenics, 7:179-188, 1936.
3. A. Globerson and S. Roweis. Metric learning by collapsing classes. In Y. Weiss, B. Schölkopf, and J. Platt, editors, Advances in Neural Information Processing Systems 18. MIT Press, Cambridge, MA, 2006.
4. J. Goldberger, S. Roweis, G. Hinton, and R. Salakhutdinov. Neighbourhood components analysis. In L. K. Saul, Y. Weiss, and L. Bottou, editors, Advances in Neural Information Processing Systems 17, 2005.
5. T. Hastie and R. Tibshirani. Discriminant adaptive nearest neighbor classification. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 18:607-616, 1996.
6. A. Mordecai. Nonlinear Programming: Analysis and Methods. Dover Publishing, 2003.
7. F. Pereira and G. Gordon. The support vector decomposition machine. In Proceedings of the International Conference on Machine Learning (ICML), 2006.
8. J. D. M. Rennie and N. Srebro. Fast maximum margin matrix factorization for collaborative prediction. In Proceedings of the 22nd International Conference on Machine Learning (ICML), 2005.
9. K. Q. Weinberger, J. Blitzer, and L. K. Saul. Distance metric learning for large margin nearest neighbor classification. In Y. Weiss, B. Schölkopf, and J. Platt, editors, Advances in Neural Information Processing Systems 18, 2006.
10. E. P. Xing, A. Y. Ng, M. I. Jordan, and S. Russell. Distance metric learning, with application to clustering with side-information. In T. G. Dietterich, S. Becker, and Z. Ghahramani, editors, Advances in Neural Information Processing Systems 14, 2002.