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Journal of Optimization
Volume 2016 (2016), Article ID 2659012, 7 pages
Research Article

Evidence Maximization Technique for Training of Elastic Nets

1Moscow Institute of Physics and Technology, Moscow 141700, Russia
2Institute for Systems Analysis, Russian Academy of Sciences, Prospekt 60-Let Octyabria 9, Moscow 117312, Russia
3MV Lomonosov Moscow State University, Leninskie Gory 1, Moscow 119991, Russia

Received 15 February 2016; Revised 10 May 2016; Accepted 15 May 2016

Academic Editor: Manlio Gaudioso

Copyright © 2016 Igor Dubnov et al. 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.


This paper presents a technique of evidence maximization for automatic tuning of regularization parameters of elastic nets, which allows tuning many parameters simultaneously. This technique was applied to handwritten digit recognition. Experiments showed its ability to train either models with high accuracy of recognition or highly sparse models with reasonable accuracy.