In constrained optimization problems the rates of change of the objective function with respect to the independent (nonbasic) variables have been interpreted as shadow prices, dual variables, and ...

This result is obtained by first showing that the same result holds for inequality constrained nonlinear least-squares. As a consequence, the presence of (possibly nonconvex) equality/inequality ...

Traditional variational quantum algorithms are often constrained by the optimization landscape, easily getting trapped in local minima when dealing with complex non-convex problems.