13 papers
Inertial forward-backward algorithm with exterior penalization and Tikhonov regularization
Siqi Qu, Juan Peypouquet, Mathias Staudigl
In a real Hilbertian setting, we develop in this paper numerical splitting techniques guaranteeing strong convergence to the least norm solution of constrained variational inequali…
Stochastic Differential Inclusions driven by Maximal Monotone Operators with empty interiors
Juan Guillermo Garrido, Pedro Pérez-Aros, Mathias Staudigl
This paper studies the long-time behavior of stochastic differential inclusions driven by maximal monotone operators, motivated by continuous-time models of first-order optimizatio…
A Stochastic Gradient Descent Approach to Design Policy Gradient Methods for LQR
Bowen Song, Simon Weissmann, Mathias Staudigl +1
In this work, we propose a stochastic gradient descent (SGD) framework to design data-driven policy gradient descent algorithms for the linear quadratic regulator problem. Two alte…
Stochastic variance reduced extragradient methods for solving hierarchical variational inequalities
Pavel Dvurechensky, Andrea Ebner, Johannes Carl Schnebel +2
We are concerned with optimization in a broad sense through the lens of solving variational inequalities (VIs) -- a class of problems that are so general that they cover as particu…
Extragradient methods with complexity guarantees for hierarchical variational inequalities
Pavel Dvurechensky, Meggie Marschner, Shimrit Shtern +1
In the framework of a real Hilbert space we consider the problem of approaching solutions to a class of hierarchical variational inequality problems, subsuming several other proble…
Asymptotic behaviour of coupled random dynamical systems with multiscale aspects
D. Russell Luke, Johannes-Carl Schnebel, Mathias Staudigl +2
We examine a class of stochastic differential inclusions involving multiscale effects designed to solve a class of generalized variational inequalities. This class of problems cont…