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A sparse optimization problem with hybrid $$L_2{\text {-}}L_p$$L2-Lp regularization for application of magnetic resonance brain images

Author

Listed:
  • Xuerui Gao

    (Shanghai University)

  • Yanqin Bai

    (Shanghai University)

  • Qian Li

    (Shanghai University of Engineering Science)

Abstract

Regularization techniques have been proved useful in an enormous variety of sparse optimization problem. In this paper, we introduce a new formulation of regularization with a hybrid $$L_2{\text {-}}L_p~(0

Suggested Citation

  • Xuerui Gao & Yanqin Bai & Qian Li, 0. "A sparse optimization problem with hybrid $$L_2{\text {-}}L_p$$L2-Lp regularization for application of magnetic resonance brain images," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-25.
    • Handle: RePEc:spr:jcomop:v::y::i::d:10.1007_s10878-019-00479-x
    DOI: 10.1007/s10878-019-00479-x
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    References listed on IDEAS

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    6. Liwei Zhong & Yanqin Bai, 2019. "Three-sided stable matching problem with two of them as cooperative partners," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 286-292, January.
    7. Fan J. & Li R., 2001. "Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1348-1360, December.
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