Non-Euclidean proximal methods for convex-concave saddle-point problems
Non-Euclidean proximal methods for convex-concave saddle-point problems
Motivated by the flexibility of the Proximal Alternating Predictor Corrector (PAPC) algorithm which can tackle a broad class of structured constrained convex optimization problems via their convexconcave saddle-point reformulation, in this paper, we extend the scope of the PAPC algorithm to include non-Euclidean proximal steps.This allows for adapting to the …