Matching pursuit approach to sparse gaussian process regression

Abstract

A system and method is provided for supervised learning. A training set is provided to the system. The system selects a training element from the provided training set, and adds the training element to a basis element set I. The system conducts an optimization test on the basis element set I with the selected training element to produce a selection score. The system determines whether the selection score indicates an improvement in optimization for the basis element set I. The system discards the selected element if the selection score does not indicate an improvement, and keeps the selected element if the selection score does indicate improvement. The process may then be repeated for other training elements until either the specified maximum number of basis functions is reached or improvement in optimization is below a threshold. At that point, the chosen set I should represent an optimized basis set.