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Abstract and Applied Analysis
Volume 2012, Article ID 436510, 16 pages
Research Article

Consistency Analysis of Spectral Regularization Algorithms

Shandong Provincial Key Laboratory of Network based Intelligent Computing, School of Mathematic Science, University of Jinan, Jinan 250022, China

Received 10 January 2012; Revised 30 March 2012; Accepted 16 April 2012

Academic Editor: Ondřej Došlý

Copyright © 2012 Yukui Zhu 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.


We investigate the consistency of spectral regularization algorithms. We generalize the usual definition of regularization function to enrich the content of spectral regularization algorithms. Under a more general prior condition, using refined error decompositions and techniques of operator norm estimation, satisfactory error bounds and learning rates are proved.