  We show that the iterates generated by a generic first-order meta-algorithm
satisfy a canonical perturbed Fenchel duality inequality. The latter in turn
readily yields a unified derivation of the best known convergence rates for
various popular first-order algorithms including the conditional gradient
method as well as the main kinds of Bregman proximal methods: subgradient,
gradient, fast gradient, and universal gradient methods.
