An Efficient and Globally Convergent Algorithm for ${\ell }_{p,q}$-${\ell }_r$ Model in Group Sparse Optimization

Abstract

Group sparsity combines the underlying sparsity and group structure of the data in problems. We develop a proximally linearized algorithm InISSAPL for the non-Lipschitz group sparse ${\ell }_{p,q}$-${\ell }_r$ optimization problem.