Sequential safe feature elimination rule for L1-regularized regression with Kullback–Leibler divergence

Author:

Wang Hongmei,Jiang Kun,Xu YitianORCID

Funder

National Natural Science Foundation of China

Natural Science Foundation of Beijing Municipality

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference39 articles.

1. Atamturk, A., & Gomez, A. (2020). Safe screening rules for l0-regression from perspective relaxations. In Proceedings of the 37th international conference on machine learning (pp. 421–430).

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3. A full migration BBO algorithm with enhanced population quality bounds for multimodal biomedical image registration;Chen;Applied Soft Computing,2020

4. Safe feature screening rules for the regularized huber regression;Chen;Applied Mathematics and Computation,2020

5. Expanding boundaries of gap safe screening;Dantas,2021

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