Similarity learning for provably accurate sparse linear classification

Proceedings of the 29th International Conference on Machine Learning, ICML 2012

Volumn 2, Issue , 2012, Pages 1871-1878

  Bellet, Aurélien ^a   Habrard, Amaury ^a   Sebban, Marc ^a  

^a UNIVERSITÉ JEAN MONNET   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION ERRORS; DATA SETS; FORMAL FRAMEWORK; GENERALIZATION BOUND; K-NN ALGORITHM; LINEAR CLASSIFICATION; LINEAR CLASSIFIERS; MAHALANOBIS DISTANCES; NONLINEAR FEATURES; OVERFITTING; SIMILARITY FUNCTIONS; SPARSE CLASSIFIERS; STATE OF THE ART; STATE-OF-THE-ART METHODS; UNIFORM STABILITY;

LEARNING SYSTEMS; OPTIMIZATION; PATTERN RECOGNITION;

LEARNING ALGORITHMS;

EID: 84867114766     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. Balcan, M.-F., Blum, A., and Srebro, N. Improved Guarantees for Learning via Similarity Functions. In COLT, pp. 287-298, 2008.
2. Bousquet, O. and Elisseeff, A. Stability and Generalization. JMLR, 2:499-526, 2002.
3. Chatpatanasiri, R., Korsrilabutr, T., Tangchanachaianan, P., and Kijsirikul, B. A new kernelization framework for Mahalanobis distance learning algorithms. Neurocomputing, 73:1570-1579, 2010.
4. Chechik, G., Shalit, U., Sharma, V., and Bengio, S. An Online Algorithm for Large Scale Image Similarity Learning. In NIPS, pp. 306-314, 2009.
5. Davis, J. V., Kulis, B., Jain, P., Sra, S., and Dhillon, I. S. Information-theoretic metric learning. In ICML, pp. 209-216, 2007.
6. Jain, P., Kulis, B., Dhillon, I. S., and Grauman, K. Online Metric Learning and Fast Similarity Search. In NIPS, pp. 761-768, 2008.
7. Kar, P. and Jain, P. Similarity-based Learning via Data Driven Embeddings. In NIPS, 2011.
8. Qamar, A. M. Generalized Cosine and Similarity Metrics: A supervised learning approach based on nearest-neighbors. PhD thesis, University of Grenoble, 2010.
9. Schölkopf, B., Smola, A., and Mller, K.-R. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation, 10(1):1299-1319, 1998.
10. Schultz, M. and Joachims, T. Learning a Distance Metric from Relative Comparisons. In NIPS, 2003.
11. Shalev-Shwartz, S., Singer, Y., and Ng, A. Y. Online and batch learning of pseudo-metrics. In ICML, 2004.
12. Weinberger, K. Q. and Saul, L. K. Distance Metric Learning for Large Margin Nearest Neighbor Classification. JMLR, 10:207-244, 2009.
13. Ying, Y., Huang, K., and Campbell, C. Sparse Metric Learning via Smooth Optimization. In NIPS, pp. 2214-2222, 2009.
14. Zhu, J., Rosset, S., Hastie, T., and Tibshirani, R. 1-norm Support Vector Machines. In NIPS, volume 16, pp. 49-56, 2003.