1 citations · 1 across the 16 of their papers we have counts for
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Derivative-free stochastic bilevel optimization for inverse problems
Mathias Staudigl, Simon Weissmann, Tristan van Leeuwen
Inverse problems are key issues in several scientific areas, including signal processing and medical imaging. Data-driven approaches for inverse problems aim for learning model and…
An Online Feasible Point Method for Benign Generalized Nash Equilibrium Problems
Sarah Sachs, Hedi Hadiji, Tim van Erven +1
We consider a repeatedly played generalized Nash equilibrium game. This induces a multi-agent online learning problem with joint constraints. An important challenge in this setting…
Barrier Algorithms for Constrained Non-Convex Optimization
Pavel Dvurechensky, Mathias Staudigl
In this paper we theoretically show that interior-point methods based on self-concordant barriers possess favorable global complexity beyond their standard application area of conv…
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…
Tikhonov regularized exterior penalty dynamics for constrained variational inequalities
Siqi Qu, Mathias Staudigl
Solving equilibrium problems under constraints is an important problem in optimization and optimal control. In this context an important practical challenge is the efficient incorp…