group variable selection

A Generalized Formulation for Group Selection via ADMM

  • Chengyu Ke
  • Sunyoung Shin
  • Yifei Lou
  • Miju Ahn
    • Categories Nonlinear Optimization Tags , , ,

    This paper studies a statistical learning model where the model coefficients have a pre-determined non-overlapping group sparsity structure. We consider a combination of a loss function and a regularizer to recover the desired group sparsity patterns, which can embrace many existing works. We analyze the stationary solution of the proposed formulation, obtaining a sufficient condition … Read more

    Joint Variable Selection for Data Envelopment Analysis via Group Sparsity

  • Zhiwei (Tony) Qin
  • Irene Song
    • Categories Applications - OR and Management Sciences, Convex Optimization Tags , , ,

    This study develops a data-driven group variable selection method for data envelopment analysis (DEA), a non-parametric linear programming approach to the estimation of production frontiers. The proposed method extends the group Lasso (least absolute shrinkage and selection operator) designed for variable selection on (often predefined) groups of variables in linear regression models to DEA models. … Read more