Learning curves for multi-task Gaussian process regression

no code implementations • NeurIPS 2012 • Peter Sollich, Simon Ashton

We study the average case performance of multi-task Gaussian process (GP) regression as captured in the learning curve, i. e.\ the average Bayes error for a chosen task versus the total number of examples $n$ for all tasks.

Multi-Task Learning regression