Most existing approaches for non-parametric kernel learning (NPKL) suer from expensive computation, which would limit their applications to large-scale problems. To address the scalability problem of NPKL, we propose a novel algorithm called BCDNPKL, which is very ecient and scalable. Superior to most
['Enliang Hu', 'Bo Wang', 'Songcan Chen']
BCDNPKL: Scalable Non-Parametric Kernel Learning Using Block Coordinate Descent