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Recently, metric learning and similarity learning have attracted a large amount of interest.
C. McDiarmid. Surveys in Combinatorics, Chapter On the methods of bounded differences, 148-188, 1989. Cambridge University Press, Cambridge (UK)
1989
Earlier work this paper cites.
M. Ledoux and M. Talagrand. Probability in Banach Spaces: Isoperimetry and Processes
1991
Earlier work this paper cites.
V.H. De La Peña and E. Giné. Decoupling: from Dependence to Independence
1999
Earlier work this paper cites.
P.L. Bartlett and S. Mendelson. Rademacher and Gaussian complexities: risk bounds and structural results. J. of Machine Learning Research
2002
Earlier work this paper cites.
O. Bousquet and A. Elisseeff. Stability and generalization. J. of Machine Learning Research
2002
Earlier work this paper cites.
Empirical margin distributions and bounding the generalization error of combined classifiers
V. Koltchinskii and V. Panchenko · 2002
Earlier work this paper cites.
E. Xing, A. Ng, M. Jordan, and S. Russell. Distance metric learning with application to clustering with side information. NIPS
2002
Earlier work this paper cites.
D.R. Chen, Q. Wu, Y. Ying and D.X. Zhou. Support vector machine soft margin classifiers: error analysis, J. of Machine Learning Research
2004
Earlier work this paper cites.
J. Goldberger, S. Roweis, G. Hinton, and R. Salakhutdinov. Neighbourhood component analysis. NIPS
2004
Earlier work this paper cites.
A. Bar-Hillel, T. Hertz, N. Shental, and D. Weinshall. Learning a mahalanobis metric from equivalence constraints. J. of Machine Learning Research
2005
Earlier work this paper cites.
A. Globerson and S. Roweis. Metric learning by collapsing classes. NIPS
2005
Earlier work this paper cites.
S. C. H. Hoi, W. Liu, M. R. Lyu, and W.-Y. Ma. Learning distance metrics with contextual constraints for image retrieval. CVPR
2006
Cited alongside, same era.
R. Rosales and G. Fung. Learning sparse metrics via linear programming, KDD
2006
Cited alongside, same era.
J. Davis, B. Kulis, P. Jain, S. Sra, and I. Dhillon. Information-theoretic metric learning. ICML
2007
Cited alongside, same era.
L. Torresani and K. Lee. Large margin component analysis. NIPS
2007
Cited alongside, same era.
L. Yang and R. Jin. Distance metric learning: A comprehensive survey. In Technical report, Department of Computer Science and Engineering, Michigan State University
2007
Cited alongside, same era.
S. Clémencon, G. Lugosi, and N. Vayatis. Ranking and empirical minimization of U-statistics. The Annals of Statistics
C. Shen, J. Kim, L. Wang and A. Hengel. Positive semidefinite metric learning with boosting. NIPS
2009
Later among the works it cites.
Y. Ying, K. Huang and C. Campbell. Sparse metric learning via smooth optimisation. NIPS
2009
Later among the works it cites.
Y. Ying and Campbell. Generalization bounds for learning the kernel. COLT
2009
Later among the works it cites.
G. Chechik, V. Sharma, U. Shalit, and S. Bengio. Large scale online learning of image similarity through ranking. J. of Machine Learning Research
2010
Later among the works it cites.
O. Shalit, D. Weinshall and G. Chechik. Online learning in the manifold of low-rank matrices. NIPS
2010
Later among the works it cites.
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2008
Cited alongside, same era.
A. Maurer. Learning similarity with operator-valued large-margin classifiers, J. of Machine Learning Research
2008
Cited alongside, same era.
K. Q. Weinberger and L. K. Saul. Fast solvers and efficient implementations for distance metric learning. ICML
2008
Cited alongside, same era.
M. Guillaumin, J. Verbeek and C. Schmid. Is that you? Metric learning approaches for face identification. ICCV
2009
Cited alongside, same era.
R. Jin, S. Wang and Y. Zhou. Regularized distance metric learning: theory and algorithm. NIPS
2009
Cited alongside, same era.
2010
Later among the works it cites.
B. McFee and G. Lanckriet. Learning multi-modal similarity. J. of Machine Learning Research
2011
Later among the works it cites.
P. Kar and P. Jain. Similarity-based learning via data-driven embeddings. NIPS
2011
Later among the works it cites.
V. Koltchinskii. Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems. Springer, 2011
2011
Later among the works it cites.
Y. Ying and P. Li. Distance metric learning with eigenvalue optimisation. J. of Machine Learning Research
2012
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