The idea of gradient boosting originated in the observation by Leo Breiman that boosting can be interpreted as an optimization algorithm on a suitable cost function.[1] Explicit regression gradient boosting algorithms were subsequently developed by Jerome H. Friedman,[2][3] simultaneously with the more general functional gradient boosting perspective of Llew Mason, Jonathan Baxter, Peter Bartlett and Marcus Frean.[4][5] The later two papers introduced the view of boosting algorithms as iterative functional gradient descent algorithms.