Guided by an initial idea of building a complex (non linear) decision surface with maximal local margin in input space, we give a possible geometrical intuition as to why K-Neares...
Compressive sensing accurately reconstructs a signal that is sparse in some basis from measurements, generally consisting of the signal’s inner products with Gaussian random vec...
Abstract-- Using the kernel trick idea and the kernels as features idea, we can construct two kinds of nonlinear feature spaces, where linear feature extraction algorithms can be e...