Potential games in volatile environments. - Mathias Staudigl (Games Econ. Behav., 2011)

Stochastic stability in asymmetric binary choice coordination games. - Mathias Staudigl (Games Econ. Behav., 2012)

Co-evolutionary dynamics and Bayesian interaction games. - Mathias Staudigl (Int. J. Game Theory, 2013)

Evolution of social networks. - Tim Hellmann; Mathias Staudigl (Eur. J. Oper. Res., 2014)

Constrained interactions and social coordination. - Mathias Staudigl; Simon Weidenholzer (J. Econ. Theory, 2014)

Convergence to nash equilibrium in continuous games with noisy first-order feedback. - Panayotis Mertikopoulos; Mathias Staudigl (CDC, 2017)

Learning in time-varying games. - Benoit Duvocelle; Panayotis Mertikopoulos; Mathias Staudigl; Dries Vermeulen (CoRR, 2018)

Stochastic Mirror Descent Dynamics and Their Convergence in Monotone Variational Inequalities. - Panayotis Mertikopoulos; Mathias Staudigl (J. Optim. Theory Appl., 2018)

Sample Path Large Deviations for Stochastic Evolutionary Game Dynamics. - William H. Sandholm; Mathias Staudigl (Math. Oper. Res., 2018)

On the Convergence of Gradient-Like Flows with Noisy Gradient Input. - Panayotis Mertikopoulos; Mathias Staudigl (SIAM J. Optim., 2018)

Forward-backward-forward methods with variance reduction for stochastic variational inequalities. - Radu Ioan Bot; Panayotis Mertikopoulos; Mathias Staudigl; Phan Tu Vuong (CoRR, 2019)

Generalized Self-concordant Hessian-barrier algorithms. - Pavel E. Dvurechensky; Mathias Staudigl; César A. Uribe (CoRR, 2019)

Inducing strong convergence of trajectories in dynamical systems associated to monotone inclusions with composite structure. - Radu Ioan Bot; Sorin-Mihai Grad; Dennis Meier; Mathias Staudigl (CoRR, 2019)

Hessian Barrier Algorithms for Linearly Constrained Optimization Problems. - Immanuel M. Bomze; Panayotis Mertikopoulos; Werner Schachinger; Mathias Staudigl (SIAM J. Optim., 2019)

Distributed forward-backward (half) forward algorithms for generalized Nash equilibrium seeking. - Barbara Franci; Mathias Staudigl; Sergio Grammatico (ECC, 2020)

Self-Concordant Analysis of Frank-Wolfe Algorithms. - Pavel E. Dvurechensky; Petr Ostroukhov; Kamil Safin; Shimrit Shtern; Mathias Staudigl (ICML, 2020)

Computing Dynamic User Equilibrium on Large-Scale Networks Without Knowing Global Parameters. - Duong Viet Thong; Aviv Gibali; Mathias Staudigl; Phan Tu Vuong (CoRR, 2020)

A relaxed-inertial forward-backward-forward algorithm for stochastic generalized Nash equilibrium seeking. - Shisheng Cui; Barbara Franci; Sergio Grammatico; Uday V. Shanbhag; Mathias Staudigl (CDC, 2021)

Equilibrium Tracking and Convergence in Dynamic Games. - Panayotis Mertikopoulos; Mathias Staudigl (CDC, 2021)

A privacy-preserving distributed computational approach for distributed locational marginal prices. - Olivier Bilenne; Paulin Jacquot; Nadia Oudjane; Mathias Staudigl; Cheng Wan 001 (CoRR, 2021)

First-Order Methods for Convex Optimization. - Pavel E. Dvurechensky; Shimrit Shtern; Mathias Staudigl (EURO J. Comput. Optim., 2021)

A Privacy-preserving Decentralized Algorithm for Distribution Locational Marginal Prices. - Olivier Bilenne; Barbara Franci; Paulin Jacquot; Nadia Oudjane; Mathias Staudigl; Cheng Wan 001 (CDC, 2022)

Proximal-like algorithms for equilibrium seeking in mixed-integer Nash equilibrium problems. - Filippo Fabiani; Barbara Franci; Simone Sagratella; Martin Schmidt 003; Mathias Staudigl (CDC, 2022)

A competitive search game with a moving object. - János Flesch; Benoit Duvocelle; Hui Min Shi; Mathias Staudigl; Dries Vermeulen (ISAIM, 2022)

Stochastic relaxed inertial forward-backward-forward splitting for monotone inclusions in Hilbert spaces. - Shisheng Cui; Uday V. Shanbhag; Mathias Staudigl; Phan Tu Vuong (Comput. Optim. Appl., 2022)

A conditional gradient homotopy method with applications to Semidefinite Programming. - Pavel E. Dvurechensky; Shimrit Shtern; Mathias Staudigl (CoRR, 2022)

Distributed Random Block-Coordinate descent methods for ill-posed composite convex optimisation problems. - Mathias Staudigl; Paulin Jacquot (CoRR, 2022)

Mini-Batch Stochastic Three-Operator Splitting for Distributed Optimization. - Barbara Franci; Mathias Staudigl (IEEE Control. Syst. Lett., 2022)

A competitive search game with a moving target. - Benoit Duvocelle; János Flesch; Mathias Staudigl; Dries Vermeulen (Eur. J. Oper. Res., 2022)

Generalized self-concordant analysis of Frank-Wolfe algorithms. - Pavel E. Dvurechensky; Kamil Safin; Shimrit Shtern; Mathias Staudigl (Math. Program., 2023)

Multiagent Online Learning in Time-Varying Games. - Benoit Duvocelle; Panayotis Mertikopoulos; Mathias Staudigl; Dries Vermeulen (Math. Oper. Res., 2023)

A relaxation-based probabilistic approach for PDE-constrained optimization under uncertainty with pointwise state constraints. - Drew P. Kouri; Mathias Staudigl; Thomas M. Surowiec (Comput. Optim. Appl., 2023)

Incentive compatibility in sender-receiver stopping games. - Aditya Aradhye; János Flesch; Mathias Staudigl; Dries Vermeulen (Games Econ. Behav., 2023)

Barrier Algorithms for Constrained Non-Convex Optimization. - Pavel E. Dvurechensky; Mathias Staudigl (ICML, 2024)

Tikhonov Regularized Exterior Penalty Dynamics for Constrained Variational Inequalities. - Mathias Staudigl; Siqi Qu (IEEE Control. Syst. Lett., 2024)

An Online Feasible Point Method for Benign Generalized Nash Equilibrium Problems. - Sarah Sachs; Hédi Hadiji; Tim van Erven; Mathias Staudigl (ALT, 2025)

Hessian barrier algorithms for non-convex conic optimization. - Pavel E. Dvurechensky; Mathias Staudigl (Math. Program., 2025)

A Regularized Variance-Reduced Modified Extragradient Method for Stochastic Hierarchical Games. - Shisheng Cui; Uday V. Shanbhag; Mathias Staudigl (J. Optim. Theory Appl., 2025)