A Hybrid Monte Carlo Architecture for Parameter Optimization

10 May 2014James Brofos

Much recent research has been conducted in the area of Bayesian learning, particularly with regard to the optimization of hyper-parameters via Gaussian process regression. The methodologies rely chiefly on the method of maximizing the expected improvement of a score function with respect to adjustments in the hyper-parameters... (read more)

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