Beyond the Golden Ratio for Variational Inequality Algorithms

no code implementations • 28 Dec 2022 • Ahmet Alacaoglu, Axel Böhm, Yura Malitsky

We improve the understanding of the $\textit{golden ratio algorithm}$, which solves monotone variational inequalities (VI) and convex-concave min-max problems via the distinctive feature of adapting the step sizes to the local Lipschitz constants.

Two steps at a time --- taking GAN training in stride with Tseng's method

no code implementations • 1 Jan 2021 • Axel Böhm, Michael Sedlmayer, Ernö Robert Csetnek, Radu Ioan Bot

Motivated by the training of Generative Adversarial Networks (GANs), we study methods for solving minimax problems with additional nonsmooth regularizers.