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Co-authored by Max L.N. Goncalves and Renato D.C. Monteiro

In this talk, we present a regularized variant of the alternating direction method of multipliers (ADMM) for solving linearly constrained convex programs. The pointwise iteration-complexity of the new variant is better than the corresponding one for the standard ADMM method and, up to a logarithmic term, is identical to the ergodic iteration-complexity of the latter method. We discuss how this regularized ADMM can be seen as an instance of a regularized hybrid proximal extragradient framework whose error condition at each iteration includes both a relative error and a summable error.