NanaAkwasiAbayieBoateng/Optimization-Methods-for-Tuning-Predictive-Models

Code and slides from a 2016 talk at the Cambridge UK RUG

Optimization Methods for Tuning Predictive Models

This repo has code and slides from a 2016 talk at the Cambridge UK RUG.

References

• Brochu, E., Cora, V. M., & De Freitas, N. (2010). A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning. arXiv.
• Kuhn, M., & Johnson, K. (2013). Applied Predictive Modeling. Springer Verlag.
• Rasmussen, C. E., & Williams, C. K. I. (2006). Gaussian Processes for Machine Learning. MIT Press.
• Smola, A., & Scholkopf, B. (2004). A tutorial on support vector regression. Statistics and Computing, 14(3), 199222.
• Smola, A., Vapnik, V. (1997). Support vector regression machines. Advances in neural information processing systems, 9, 155-161.
• Snoek, J., Larochelle, H., Adams, R. P. (2012). Practical Bayesian optimization of machine learning algorithms. In Advances in neural information processing systems (pp. 2951-2959).