In this paper, we study the convergence of iterative hard-thresholding algorithm with continuation for solving the \(\ell ^0\)-regularized minimization. A decreasing continuation strategy is used for the regularization parameter. By using the Kurdyka–Łojasiewicz property, we prove that the algorithm globally converges to a critical point of a known objective function. Numerical results are also presented.
['Tao Sun', 'Lizhi Cheng']
Convergence of iterative hard-thresholding algorithm with continuation