Yago R. Aguado-Carrillo-de-Albornoz

Revisiting Thinning Methods for Kernel Learning Problems

Backward Kernel Herding is introduced, an algorithm that addresses the problem of iteratively removing points from the dataset by iteratively removing points from the dataset, achieving results comparable to current state-of-the-art approaches while accelerating the subsampling process in realistic scenarios where the...