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math.OC2026
On the Convergence of Proximal Algorithms for Weakly-convex Min-max Optimization
Guido Tapia-Riera, Camille Castera, Nicolas Papadakis
We study alternating first-order algorithms with no inner loops for solving nonconvex-strongly-concave min-max problems. We show the convergence of the alternating gradient descent…
math.OC2024
Near-optimal Closed-loop Method via Lyapunov Damping for Convex Optimization
Severin Maier, Camille Castera, Peter Ochs
We introduce an autonomous system with closed-loop damping for first-order convex optimization. While, to this day, optimal rates of convergence are almost exclusively achieved by…