Software

 

·         Stochastic Online AUC Maximization (SOLAM): MATLAB code

Reference

Y. Ying, L. Wen and S. Lyu.  Stochastic online AUC maximization.  NIPS, 2016.


·         Sub-SML: MATLAB code  (drop me an email for LBP and SIFT PCA-reduced features)

Reference

1.     Q. Cao, Y. Ying and Peng Li, Similarity metric learning for face recognitionIEEE International Conference on Computer Vision (ICCV), 2013.


·         Eigenvalue optimization for metric learning: MATLAB code

Reference

1.     Y. Ying and P. Li, Distance metric learning with eigenvalue optimization, Journal of Machine Learning Research, 13 (1) 1-26, 2012.

 


·        Sparse metric learning:  MATLAB code (version 1)

References

1.     Y. Ying and K. Huang, Distance metric learning with sparse regularization , Preprint, University of Exeter, September, 2010.


·        Smooth optimization for SVM Classification with indefinite kernels: MATLAB code (version 1)

    

    References

1.     R. Luss and A. d'Aspremont, Support vector machine classification with indefinite kernels, NIPS 2007

2.     Y. Ying, C. Campbell and M. Girolami, Analysis of SVM with indefinite kernels, NIPS, 2009.


·        Information-theoretic kernel integration: Matlab code coming soon!

     References

1.     Y. Ying, K. Huang and C. Campbell, Enhanced protein fold recognition through a novel data integration approach, BMC Bioinformatics (Open access), (2009) 10:267.


·        Variational Bayesian approach for LPD clustering model: MATLAB code

 

This software is based on [1,2] which provides variational Bayesian approaches and its collapsed variants for Latent Process Decomposition (LPD) model [3].

References

1.     Y. Ying, A note on variational Bayesian inference, Manuscript, 2007.

2.     Y.Ying, Peng Li and C. Campbell, A marginalized variational Bayesian approach to the analysis of array data, BMC Proceedings of the Workshop on Machine Learning in Systems Biology, 2007.

3.     S. Rogers, M. Girolami, C. Campbell, and R. Breitling, The Latent Process Decomposition of cDNA Microarray Datasets. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2 (2005) 143-156.


·        Learning coordinate gradients: Matlab code

 


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