array(2) { ["lab"]=> string(4) "1409" ["publication"]=> string(5) "12496" } Robust regularization theory based on Lq (0< q< 1) regularization: The asymptotic distribution and variable selection consistence of solutions - Liang Yong | LabXing

Liang Yong

简介 中藥質量控制資訊系統，生物資訊學

大学 Macau University of Science and Technology / Faculty of Information Technology
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Robust regularization theory based on Lq (0< q< 1) regularization: The asymptotic distribution and variable selection consistence of solutions

2010
期刊 Sci Sin Mat
In this paper, we introduce the robust L q (0 q∞) regularization model, and then prove the global asymptotic distribution theorem for solutions of the model we propose. Applying the results, we can derive the model based on L q (0 q 1) regularization satisfying the consistent property of variable selection; in other words, it has the capacity of variable selection. To solve this model, we develop an iterative weighted algorithm without extra parameters, and give the corresponding strategy of selecting regularization parameters. The experiment results reveal that the algorithm we introduce is available, efficient and widely valuable.

  • 卷 40
  • 期 10
  • 页码 985-998
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