Ángela Fernández-Pascual

Revisiting Thinning Methods for Kernel Learning Problems

Kernel methods are widely used because of their strong theoretical guarantees and empirical performance. However, their high computational cost limits their applicability to large-scale datasets. To address this shortcoming, several approaches use Maximum Mean Discrepancy to construct representative subsets that preser...