The Learning Rates of Regularized Regression Based on Reproducing Kernel Banach Spaces

Abstract

We study the convergence behavior of regularized regression based on reproducing kernel Banach spaces (RKBSs). The convex inequality of uniform convex Banach spaces is used to show the robustness of the optimal solution with respect to the distributions. The learning rates are derived in terms of the covering number and $K$-functional.