On Convergence Properties of Algorithms for Unconstrained Minimization
Mike Todd · IMA Journal of Numerical Analysis · 1989
Suppose F is a convex function on R" for which there is a sequence of points on which the function values are bounded below and the gradients converge to zero. Is it possible that F is unbounded below? The answer, perhaps surprisingly, is yes for n > 1.