Regularized Least Square Regression with Unbounded and Dependent Sampling

Xiaorong Chu and Hongwei Sun

Abstract and Applied Analysis, 2013, vol. 2013, issue 1

Abstract: This paper mainly focuses on the least square regression problem for the α‐mixing and ϕ‐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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https://doi.org/10.1155/2013/139318

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Persistent link: https://EconPapers.repec.org/RePEc:wly:jnlaaa:v:2013:y:2013:i:1:n:139318

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