## Accelerated projected gradient algorithms for sparsity constrained optimization problems

\(\) We consider the projected gradient algorithm for the nonconvex best subset selection problem that minimizes a given empirical loss function under an \(\ell_0\)-norm constraint. Through decomposing the feasible set of the given sparsity constraint as a finite union of linear subspaces, we present two acceleration schemes with global convergence guarantees, one by same-space extrapolation … Read more