5 papers
Asymmetric regularization mechanism for GAN training with Variational Inequalities
Spyridon C. Giagtzoglou, Mark H. M. Winands, Barbara Franci
We formulate the training of generative adversarial networks (GANs) as a Nash equilibrium seeking problem. To stabilize the training process and find a Nash equilibrium, we propose…
Finite-sample guarantees for data-driven forward-backward operator methods
Filippo Fabiani, Barbara Franci
We establish finite sample certificates on the quality of solutions produced by data-based forward-backward (FB) operator splitting schemes. As frequently happens in stochastic reg…
On data-driven Wasserstein distributionally robust Nash equilibrium problems with heterogeneous uncertainty
Georgios Pantazis, Barbara Franci, Sergio Grammatico
We study stochastic Nash equilibrium problems subject to heterogeneous uncertainty on the expected valued cost functions of the individual agents, where we assume no prior knowledg…
Actively learning equilibria in Nash games with misleading information
Barbara Franci, Filippo Fabiani, Alberto Bemporad
We develop a scheme based on active learning to compute equilibria in a generalized Nash equilibrium problem (GNEP). Specifically, an external observer (or entity), with little kno…
A Gauss-Seidel method for solving multi-leader-multi-follower games
Barbara Franci, Filippo Fabiani, Martin Schmidt +1
We design a computational approach to find equilibria in a class of Nash games possessing a hierarchical structure. By using tools from mixed-integer optimization and the character…