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

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 ${\mathrm{\ell }}_{p,q}$-${\mathrm{\ell }}_r$ optimization problem.