  This paper considers a general convex constrained problem setting where
functions are not assumed to be differentiable nor Lipschitz continuous. Our
motivation is in finding a simple first-order method for solving a wide range
of convex optimization problems with minimal requirements. We study the method
of weighted dual averages (Nesterov, 2009) in this setting and prove that it is
an optimal method.
