Capacity dependent estimations by integral operator techniques

In this paper, we study the learning performance of least square regularized regression based on some capacity conditions. An iid setting is considered, where the sequence of probability measures for sampling is identical and the samples are independently drawn. We improve the learning rate to O(m^-β/(1+2β)) by integral operator techniques.