2024
Wasserstein Gradient Boosting: A Framework for Distribution-Valued Supervised Learning
NeurIPS 2024poster
Gradient boosting is a sequential ensemble method that fits a new weaker learner to pseudo residuals at each iteration. We propose Wasserstein gradient boosting, a novel extension of gradient boosting, which fits a new weak learner to alternative pseudo residuals that are Wasserstein gradients of lo…