Copyright © 2013 Xiaorong Chu and Hongwei Sun. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper mainly focuses on the least square regression problem for the -mixing and -mixing processes. The standard bound assumption for output data is abandoned and the learning algorithm is implemented with samples drawn from dependent sampling process with a more general output data condition. Capacity independent error bounds and learning rates are deduced by means of the integral operator technique.