Complexity of Partially Separable Convexly Constrained Optimization with Non-Lipschitzian Singularities

An adaptive regularization algorithm using high-order models is proposed for solving partially separable convexly constrained nonlinear optimization problems whose objective function contains non-Lipschitzian $\ell_q$-norm regularization terms for $q\in (0,1)$. It is shown that the algorithm using a... View More