  The paper proposes a heterogeneous push-sum based subgradient algorithm for
multi-agent distributed convex optimization in which each agent can arbitrarily
switch between subgradient-push and push-subgradient at each time. It is shown
that the heterogeneous algorithm converges to an optimal point at an optimal
rate over time-varying directed graphs.
