Alvarez, M. and Lawrence, N.D., Sparse convolved Gaussian processes for multi-output regression. In Proceedings of the Advances in Neural Information Processing Systems, pp. 57--64, 2009.
Anderson, T.W., An introduction to multivariate statistical analysis (2 edn), 1984, Wiley.
Arnold, S.F., The theory of linear models and multivariate analysis, 1981, Wiley.
Ben-Shimon, D. and Shmilovici, A., Accelerating the relevance vector machine via data partitioning. Foundations of Computing and Decision Sciences, 2006, 31, 27--41.
Bonilla, E.V., Chai, K.M.A. and Williams, C.K.I., Multi-task Gaussian process prediction. In Proceedings of the Advances in Neural Information Processing Systems, pp. 153--160, 2007.
Boyle, P. and Frean, M.R., Dependent Gaussian Processes.. In Proceedings of the Advances in Neural Information Processing Systems, pp. 217--224, 2004.
Catanzaro, B., Sundaram, N. and Keutzer, K., Fast support vector machine training and classification on graphics processors. In Proceedings of the Proceedings of the 25th international conference on Machine learning, pp. 104--111, 2008. [OpenAIRE]
Chang, C.C. and Lin, C.J., LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2011, 2, 27:1--27.
Chu, W., Keerthi, S.S. and Ong, C.J., Bayesian support vector regression using a unified loss function. IEEE Transactions on Neural Networks, 2004, 15, 29--44. [OpenAIRE]
Cortes, C. and Vapnik, V., Support-vector networks. Machine learning, 1995, 20, 273--297.
Gao, J.B., Gunn, S.R., Harris, C.J. and Brown, M., A probabilistic framework for SVM regression and error bar estimation. Machine Learning, 2002, 46, 71--89.
Gibbs, M., Bayesian Gaussian processes for classification and regression. PhD thesis, University of Cambridge, 1997.
Gramacy, R.B., Niemi, J. and Weiss, R.M., Massively parallel approximate Gaussian process regression. SIAM/ASA Journal on Uncertainty Quantification, 2014, 2, 564--584.
Guo, G. and Zhang, J.S., Reducing examples to accelerate support vector regression. Pattern Recognition Letters, 2007, 28, 2173--2183.
Montgomery, D.C., Applied Statistics and Probability for Engineers (6 edn), 2013, Wiley.