Argyriou, A., Evgeniou, T., and Pontil, M. (2006). Multi-Task Feature Learning. In Schölkopf, B., Platt, J., and Hofmann, T. (eds.), Advances in Neural Information Processing Systems. Cambridge, MA: Massachusetts Institute of Technology Press.
Argyriou, A., Evgeniou, T., and Pontil, M. (2008). Convex multi-task feature learning. Machine Learning, 73, 243–272.
Ashenfelter, O. (2010). Predicting the quality and prices of Bordeaux wine. Journal of Wine Economics, 5, 40–52.
Bakker, B., and Heskes, T. (2003). Task clustering and gating for Bayesian multitask learning. Journal of Machine Learning Research, 4, 83–99.
Bishop, C. (2006). Pattern Recognition and Machine Learning. New York: Springer.
Bonilla, E., Chai, K.M., and Williams, C. (2008). Multi-task Gaussian process prediction. In Advances in Neural Information Processing Systems (NIPS), 22.
Burton, B.J., and Jacobsen, J.P. (2001). The rate of return on wine investment. Economic Inquiry, 39, 337–350.
Byron, R.P., and Ashenfelter, O. (1995). Predicting the quality of an unborn grange. The Economic Record, 71, 40–53.
Cryer, J. D. and Chan, K.S. (2008). Times Series Analysis with Applications in R. Berlin: Springer.
Duvenaud, D. (2014). Automatic model construction with Gaussian processes (Doctoral dissertation, University of Cambridge).
Fogarty, J.J. (2006). The return to Australian fine wine. European Review of Agricultural Economics, 33, 542–561.
Fogarty, J.J., and Jones, C. (2011). Return to wine: A comparison of the hedonic, repeat sales, and hybrid approaches. Australian Economic Papers, 50, 147–156.
Fogarty, J.J., and Sadler, R. (2014). To Save or savor: A review of approaches for measuring wine as an investment. Journal of Wine Economics, 9, 225–248.
Haeger, J.W., and Storchmann, K. (2006). Prices of American Pinot Noir wines: climate, craftsmanship, critics. Agricultural Economics, 35, 67–78.
Jaeger, E. (1981). To save or savor: The rate of return to storing wine: Comment. Journal of Political Economy, 89, 584–592.
Jones, G.V., and Storchmann, K. (2001). Wine market prices and investment under uncertainty: An econometric model for Bordeaux Crus Classés. Agricultural Economics, 26, 115–133.
Lawler, G. (2010). Random Walk and the Heat Equation. Student Mathematical Library, Vol. 55, American Mathematical Society, Providence, Rhode Island.
Lázaro-Gredilla, M., and Titsias, M.K. (2011). Variational heteroscedastic Gaussian process regression. In 28th International Conference on Machine Learning (ICML-11). Bellevue, WA: ACM, 841–848.
Lima, T. (2006). Price and Quality in the Californian Wine Industry: An Empirical Investigation. Journal of Wine Economics, 1, 176–190.
Masset, P., and Henderson, C. (2010). Wine as an alternative asset class. Journal of Wine Economics, 5, 87–118.
Masset, P., and Weisskopf, J.-P. (2013). Wine as an alternative asset class. In: Giraud-Heraud, E., and M. Pichery, M.-C. (eds.), Wine Economics: Quantitative Studies and Empirical Applications. New York: Palgrave Macmillan, 173–199.
Ou, P., and Wang, H. (2011). Modeling and Forecasting Stock Market Volatility by Gaussian Processes based on GARCH, EGARCH and GJR Models. Proceedings of the World Congress on Engineering, Vol 1. (London, July 6–8).
Petelin, D., Sindelar, J., Prikryl, J., and Kocijan, J. (2011). Financial modeling using Gaussian process models. In 2011 IEEE 6th International Conference on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS) (Vol. 2)., Prague, Czech Republic, 672–677.
Phuong, N.D. and Phuong, T.M. (2008). Collaborative filtering by multi-task learning. In Research, Innovation and Vision for the Future, 2008. RIVF 2008. IEEE International Conference on research, innovation and vision for the future in computing & communication technologies. University of Science, Vietnam National University Ho Chi Minh City, July 13–17, 227–232.
Rasmussen, C.E. and Williams, C.K.I. (2006). Gaussian Processes for Machine Learning. Cambridge, MA: Massachusetts Institute of Technology Press.
Ribeiro, B., and Lopes, N. (2011). Deep belief networks for financial prediction. In Lu, B.L., Zhang, L., and Kwok, J. (eds.), Neural Information Processing Proceedings, Part III. Shanghai, China, November 13–17, 766–773.
Sanning, L.W., Shaffer, S., and Sharratt, J.M. (2008). Bordeaux Wine as a financial investment. Journal of Wine Economics, 3, 51–71.
Shawe-Taylor, J., and Cristianini, N. (2004). Kernel Methods for Pattern Analysis. New York: Cambridge University Press.
Storchmann, K. (2012). Wine economics. Journal of Wine Economics, 7, 1–33.
Taylor, G.W. and Hinton, G.E. (2009). Factored conditional restricted Boltzmann Machines for modeling motion style. In Proceedings of the 26th Annual International Conference on Machine Learning. Montreal, QC, Canada, June 14–18, 1025–1032.
Wang, Y., and Khardon, R. (2012). Sparse Gaussian processes for multi-task learning. In Proceedings of the 2012 European Conference on Machine Learning and Knowledge Discovery in Databases, Volume Part 1. Bristol, UK: Springer, 711–727.
Wood, D., and Anderson, K. (2006). What determines the future value of an icon wine? Evidence from Australia. Journal of Wine Economics, 1, 141–161.
Yu, K., Tresp, V., and Schwaighofer, A. (2005). Learning Gaussian Processes from Multiple Tasks. In Proceedings of 22nd International Conference on Machine Learning (ICML), Beijing, China, 1012–1019.