Regularized Least Square Regression with Unbounded and Dependent Sampling

Xiaorong Chu and Hongwei Sun

Abstract and Applied Analysis, 2013, vol. 2013, 1-7

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.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlaaa:139318

DOI: 10.1155/2013/139318

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