Regularized Least Square Regression with Unbounded and Dependent Sampling

Xiaorong Chu, Hongwei Sun
2013 Abstract and Applied Analysis  
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.
doi:10.1155/2013/139318 fatcat:ecz5g5bj4bcapoduyzpur3uvhy