Andrea Cristofari

Full Convergence of Regularized Methods for Unconstrained Optimization

Typically, the sequence of points generated by an optimization algorithm may have multiple limit points. Under convexity assumptions, however, (sub)gradient methods are known to generate a convergent sequence of points. In this paper, we extend the latter property to a broader cl...