Proving convergence of log-linear learning in potential games. - Tatiana Tatarenko (ACC, 2014)

Log-linear learning: Convergence in discrete and continuous strategy potential games. - Tatiana Tatarenko (CDC, 2014)

A game theoretic and control theoretic approach to incentive-based demand management in smart grids. - Tatiana Tatarenko; Luis Garcia-Moreno (MED, 2014)

Finite-time behavior of log-linear learning in potential games. - Tatiana Tatarenko (NetGCooP, 2014)

1-recall reinforcement learning leading to an optimal equilibrium in potential games with discrete and continuous actions. - Tatiana Tatarenko (CDC, 2015)

Synchronous learning of efficient Nash equilibria in potential games with uncoupled dynamics and memoryless players. - Tatiana Tatarenko (ECC, 2015)

On local analysis of distributed optimization. - Tatiana Tatarenko; Behrouz Touri (ACC, 2016)

Stochastic payoff-based learning in multi-agent systems modeled by means of potential games. - Tatiana Tatarenko (CDC, 2016)

Stochastic stability of potential function maximizers in continuous version of independent log-linear learning. - Tatiana Tatarenko (ECC, 2016)

On stochastic proximal-point method for convex-composite optimization. - Angelia Nedic; Tatiana Tatarenko (Allerton, 2017)

Non-Convex Distributed Optimization. - Tatiana Tatarenko; Behrouz Touri (IEEE Trans. Autom. Control., 2017)

Game-theoretic learning and distributed optimization in memoryless multi-agent systems. - Tatiana Tatarenko (2017)

Accelerated Gradient Play Algorithm for Distributed Nash Equilibrium Seeking. - Tatiana Tatarenko; Wei Shi 010; Angelia Nedic (CDC, 2018)

Minimizing Regret in Unconstrained Online Convex Optimization. - Tatiana Tatarenko; Maryam Kamgarpour (ECC, 2018)

Minimizing Regret in Bandit Online Optimization in Unconstrained and Constrained Action Spaces. - Tatiana Tatarenko; Maryam Kamgarpour (CoRR, 2018)

Independent Log-Linear Learning in Potential Games With Continuous Actions. - Tatiana Tatarenko (IEEE Trans. Control. Netw. Syst., 2018)

Learning Nash Equilibria in Monotone Games. - Tatiana Tatarenko; Maryam Kamgarpour (CDC, 2019)

Penalized Push-Sum Algorithm for Constrained Distributed Optimization with Application to Energy Management in Smart Grid. - Tatiana Tatarenko; Jan Zimmermann; Volker Willert; Jürgen Adamy (CDC, 2019)

Optimales Energie-Management über verteilte, beschränkte Gradientenverfahren. - Jan Zimmermann; Tatiana Tatarenko; Volker Willert; Jürgen Adamy (Autom., 2019)

Stochastic learning in multi-agent optimization: Communication and payoff-based approaches. - Tatiana Tatarenko (Autom., 2019)

Learning Generalized Nash Equilibria in a Class of Convex Games. - Tatiana Tatarenko; Maryam Kamgarpour (IEEE Trans. Autom. Control., 2019)

Convergence Rate of a Penalty Method for Strongly Convex Problems with Linear Constraints. - Angelia Nedic; Tatiana Tatarenko (CDC, 2020)

Projected Push-Sum Gradient Descent-Ascent for Convex Optimization with Application to Economic Dispatch Problems. - Jan Zimmermann; Tatiana Tatarenko; Volker Willert; Jürgen Adamy (CDC, 2020)

Schnelle, verteilte Optimierungsmethoden und spieltheoretische Ansätze in vernetzten Systemen. - Tatiana Tatarenko (Autom., 2020)

Projected Push-Sum Gradient Descent-Ascent for Convex Optimizationwith Application to Economic Dispatch Problems. - Jan Zimmermann; Tatiana Tatarenko; Volker Willert; Jürgen Adamy (CoRR, 2020)

Revisiting Consensus-Based Energy-Management in Smart Grid with Transmission Losses and Directed Communication. - Jan Zimmermann; Tatiana Tatarenko; Volker Willert; Jürgen Adamy (CoRR, 2020)

Gradient Play in n-Cluster Games with Zero-Order Information. - Tatiana Tatarenko; Jan Zimmermann; Jürgen Adamy (CDC, 2021)

Gradient-Tracking over Directed Graphs for solving Leaderless Multi-Cluster Games. - Jan Zimmermann; Tatiana Tatarenko; Volker Willert; Jürgen Adamy (CoRR, 2021)

Solving leaderless multi-cluster games over directed graphs. - Jan Zimmermann; Tatiana Tatarenko; Volker Willert; Jürgen Adamy (Eur. J. Control, 2021)

A Smooth Inexact Penalty Reformulation of Convex Problems with Linear Constraints. - Tatiana Tatarenko; Angelia Nedich (SIAM J. Optim., 2021)

Geometric Convergence of Gradient Play Algorithms for Distributed Nash Equilibrium Seeking. - Tatiana Tatarenko; Wei Shi 010; Angelia Nedic (IEEE Trans. Autom. Control., 2021)

Distributed optimization methods for N-cluster games. - Tatiana Tatarenko; Jan Zimmermann (Autom., 2022)

Gradient-Tracking-basierte Lösung von Multi-Cluster-Spielen. - Jan Zimmermann; Tatiana Tatarenko; Volker Willert; Jürgen Adamy (Autom., 2022)

On the Rate of Convergence of Payoff-based Algorithms to Nash Equilibrium in Strongly Monotone Games. - Tatiana Tatarenko; Maryam Kamgarpour (CoRR, 2022)

Projected gradient-tracking in multi-cluster games and its application to power management. - Jan Zimmermann; Tatiana Tatarenko; Volker Willert; Jürgen Adamy (CoRR, 2022)

Fully Distributed Nash Equilibrium Seeking in n-Cluster Games with Zero-Order Information. - Tatiana Tatarenko (CDC, 2024)

Convergence Rate of Learning a Strongly Variationally Stable Equilibrium. - Tatiana Tatarenko; Maryam Kamgarpour (ECC, 2024)

Accelerating Distributed Nash Equilibrium Seeking. - Tatiana Tatarenko; Angelia Nedic (ECC, 2024)

Payoff-Based Learning of Nash Equilibria in Merely Monotone Games. - Tatiana Tatarenko; Maryam Kamgarpour (IEEE Trans. Control. Netw. Syst., 2024)

Convergence rate of payoff-based generalized Nash equilibrium learning. - Tatiana Tatarenko; Maryam Kamgarpour (Eur. J. Control, 2025)