Tag kernel methods
In recent years, the field of artificial neural networks (ANNs) has burgeoned, revealing complexities and characteristics that warrant deeper exploration. One such groundbreaking concept is the Neural Tangent Kernel (NTK), which significantly influences neural network convergence and generalization. This article… Continue Reading →
Nyström type subsampling approaches have garnered significant attention in large-scale kernel methods, offering potential solutions to computational challenges. In a research article titled “Less is More: Nyström Computational Regularization,” Alessandro Rudi, Raffaello Camoriano, and Lorenzo Rosasco delve into the study… Continue Reading →