3 citations · 6 across the 3 of their papers we have counts for
3 papers
math.OC2022★ 1 cited
Beyond the Golden Ratio for Variational Inequality Algorithms
Ahmet Alacaoglu, Axel Böhm, Yura Malitsky
We improve the understanding of the , which solves monotone variational inequalities (VI) and convex-concave min-max problems via the distinctive f…
math.OC2022★ 2 cited
Solving Nonconvex-Nonconcave Min-Max Problems exhibiting Weak Minty Solutions
Axel Böhm
We investigate a structured class of nonconvex-nonconcave min-max problems exhibiting so-called \emph{weak Minty} solutions, a notion which was only recently introduced, but is abl…
math.OC2020★ 3 cited
Alternating proximal-gradient steps for (stochastic) nonconvex-concave minimax problems
Radu Ioan Boţ, Axel Böhm
Minimax problems of the form have attracted increased interest largely due to advances in machine learning, in particular generative adversarial networks. Th…