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A generalized elastic net regularization with smoothed $$\ell _{q}$$ ℓ q penalty for sparse vector recovery

Author

Listed:
  • Yong Zhang

    (Shanghai University
    Jiangsu University of Science and Technology)

  • Wanzhou Ye

    (Shanghai University)

  • Jianjun Zhang

    (Shanghai University)

Abstract

In this paper, we propose an iterative algorithm for solving the generalized elastic net regularization problem with smoothed $$\ell _{q} (0

Suggested Citation

  • Yong Zhang & Wanzhou Ye & Jianjun Zhang, 2017. "A generalized elastic net regularization with smoothed $$\ell _{q}$$ ℓ q penalty for sparse vector recovery," Computational Optimization and Applications, Springer, vol. 68(2), pages 437-454, November.
    • Handle: RePEc:spr:coopap:v:68:y:2017:i:2:d:10.1007_s10589-017-9916-7
    DOI: 10.1007/s10589-017-9916-7
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    References listed on IDEAS

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    1. Zou, Hui, 2006. "The Adaptive Lasso and Its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1418-1429, December.
    2. Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
    3. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
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    Cited by:

    1. Mike K. P. So & Wing Ki Liu & Amanda M. Y. Chu, 2018. "Bayesian Shrinkage Estimation Of Time-Varying Covariance Matrices In Financial Time Series," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 369-404, December.

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