[1] Aczel A., Sounderpandian J., Complete Business Statistics. McGraw Hill, New York 2009.
[2] Atkeson C., Moore A., Schaal S., Locally weighted learning. Artificial Intelligence Review, 1997, 11, pp. 11–73.
[3] Bar-Hillel A., Hertz T., Shental N., Weinshall D., Learning a Mahalanobis metric from equivalence constraints. Journal of Machine Learning Research, 2005, 6, pp. 937–965.
[4] Cover T., Hart P., Nearest Neighbor Pattern Classification. IEEE Transactions on Information Theory, 1967, 13, pp. 21–27.
[5] Cox T.F., Cox M.A.A., Multidimensional Scaling. Chapman and Hall, London 1994.
[6] Deng Z., Chuaqui C., Singh J., Knowledge-based design of target-focused libraries using protein-ligand interaction constraints. Journal of Medicinal Chemistry, 2006, 49(2), pp. 490–500.
[7] Domeniconi C., Gunopulos D., Adaptive nearest neighbor classification using support vector machines. Advances in Neural Information Processing Systems, 2002, 14, pp. 665–672.
[8] Geppert H., Vogt M., Bajorath J., Current Trends in Ligand-Based Virtual Screening: Molecular Representations, Data Mining Methods, New Application Areas, and Performance Evaluation. Journal of Chemical Information and Modeling, 2010, 50, pp. 205–216.
[9] Goldberger J., Roweis S., Hinton G., Salakhutdinov R., Neighbourhood Components Analysis. Advances in Neural Information Processing Systems, 2004, 17, pp. 513–520.
[10] Hastie T., Tibshirani R., Discriminant Adaptive Nearest Neighbor Classification. IEEE Trans. Pattern Anal. Mach. Intell., 1996, 18, pp. 607–616.
[11] Hubert L., Arabie P., Comparing partitions. Journal of Classification, 1985, 2, pp. 193–218.
[12] Jaakkola T.S., Haussler D., Exploiting Generative Models in Discriminative Classifiers. Proceedings of the 1998 Conference on Advances in Neural Information Processing Systems II, 1999, pp. 487–493.
[13] Kedem D., Tyree S., Weinberger K.Q., Sha F., Lanckriet G., Non-linear Metric Learning. Advances in Neural Information Processing Systems, 2012, 25, pp. 2582– 2590. Available via http://books.nips.cc/papers/files/nips25/NIPS2012 1223.pdf.
[14] Klekota J., Roth F.P., Chemical Substructures That Enrich for Biological Activity. Bioinformatics 2008, 21, pp. 2518–2525.
[15] Kohavi R., A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection. Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI ’95), 1995, pp. 1137–1143.
[16] Lloyd S., Least Squares Quantization in PCM. IEEE Trans. Inf. Theor., 1982, 28, pp. 129–137.
[17] Roweis S.T., Saul L.K., Nonlinear dimensionality reduction by locally linear embedding. Science, 2000, 290, pp. 2323–2326.
[18] Scholkopf B., Smola A.J., Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. MIT Press, Cambridge, MA, 2001.
[19] Shalev-Shwartz S., Singer Y., Ng A.Y., Online and Batch Learning of Pseudometrics. Proceedings of the Twenty-first International Conference on Machine Learning (ICML ’04), 2004, pp. 743–750.
[20] Shental N., Hertz T., Weinshall D., Pavel M., Adjustment Learning and Relevant Component Analysis. Proceedings of the 7th European Conference on Computer Vision-Part IV (ECCV ’02), 2002, pp. 776–792. [21] ´Smieja M., Warszycki D., Tabor J., Bojarski A.J., Asymmetric Clustering Index in a Case Study of 5-HT1A Receptor Ligands. PloS ONE 9(7): e102069, doi:10.1371/journal.pone.0102069, 2014.
[22] Sneath P.H.A., The Application of Computers to Taxonomy. J. Gen. Microbiol., 1957, 17, pp. 201–226.
[23] Takeda H., Farsiu S. and Milanfar P., Robust kernel regression for restoration and reconstruction of images from sparse noisy data. IEEE International Conference on Image Processing, 2006, pp. 1257–1260.
[24] Xing E.P., Ng A.Y., Jordan M.I., Russell S., Distance Metric Learning, With Application To Clustering With Side-Information,. Advances in Neural Information Processing Systems, 2003, 15, pp. 505–512.
[25] Warszycki D., Mordalski S., Kristiansen K., Kafel R., Sylte I., Chilmonczyk, Z., Bojarski A. J., A Linear Combination of Pharmacophore Hypotheses as a New Tool in Search of New Active Compounds An Application for 5-HT1A Receptor Ligands. PloS ONE 8(12): e84510, doi:10.1371/journal.pone.0084510, 2013.
[26] Weinberger K.Q., Saul L.K., Distance Metric Learning for Large Margin Nearest Neighbor Classification. J. Mach. Learn. Res., 2009, 10, pp. 207–244.
[27] Weinberger K.Q., Saul L.K., Fast solvers and efficient implementations for distance metric learning. ACM International Conference Proceeding Series, 2008, 307, pp. 1160–1167.