  This paper presents smoothing schemes for obtaining approximate stationary
points of unconstrained or linearly-constrained composite nonconvex-concave
min-max (and hence nonsmooth) problems by applying well-known algorithms to
composite smooth approximations of the original problems. More specifically, in
the unconstrained (resp. constrained) case, approximate stationary points of
the original problem are obtained by applying, to its composite smooth
approximation, an accelerated inexact proximal point (resp. quadratic penalty)
method presented in a previous paper by the authors. Iteration complexity
bounds for both smoothing schemes are also established. Finally, numerical
results are given to demonstrate the efficiency of the unconstrained smoothing
scheme.
