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ORCIDTatiana Tatarenko
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2020 – today
- 2024
[c19]Tatiana Tatarenko, Angelia Nedic:
Accelerating Distributed Nash Equilibrium Seeking. ECC 2024: 323-328- [c18]Tatiana Tatarenko, Maryam Kamgarpour:
Convergence Rate of Learning a Strongly Variationally Stable Equilibrium. ECC 2024: 768-773 - 2022
- [j11]Tatiana Tatarenko, Jan Zimmermann
:
Distributed optimization methods for N-cluster games. Autom. 70(3): 237-247 (2022) - [j10]Jan Zimmermann, Tatiana Tatarenko, Volker Willert, Jürgen Adamy:
Gradient-Tracking-basierte Lösung von Multi-Cluster-Spielen. Autom. 70(4): 355-366 (2022) - [i8]Tatiana Tatarenko, Maryam Kamgarpour:
On the Rate of Convergence of Payoff-based Algorithms to Nash Equilibrium in Strongly Monotone Games. CoRR abs/2202.11147 (2022) - [i7]Jan Zimmermann, Tatiana Tatarenko, Volker Willert, Jürgen Adamy:
Projected gradient-tracking in multi-cluster games and its application to power management. CoRR abs/2202.12124 (2022) - 2021
- [j9]Jan Zimmermann, Tatiana Tatarenko, Volker Willert, Jürgen Adamy:
Solving leaderless multi-cluster games over directed graphs. Eur. J. Control 62: 14-21 (2021) - [j8]Tatiana Tatarenko, Angelia Nedich:
A Smooth Inexact Penalty Reformulation of Convex Problems with Linear Constraints. SIAM J. Optim. 31(3): 2141-2170 (2021) - [j7]Tatiana Tatarenko, Wei Shi, Angelia Nedic:
Geometric Convergence of Gradient Play Algorithms for Distributed Nash Equilibrium Seeking. IEEE Trans. Autom. Control. 66(11): 5342-5353 (2021) - [c17]Tatiana Tatarenko, Jan Zimmermann, Jürgen Adamy:
Gradient Play in n-Cluster Games with Zero-Order Information. CDC 2021: 3104-3109 - [i6]Jan Zimmermann, Tatiana Tatarenko, Volker Willert, Jürgen Adamy:
Gradient-Tracking over Directed Graphs for solving Leaderless Multi-Cluster Games. CoRR abs/2102.09406 (2021) - [i5]Tatiana Tatarenko, Jan Zimmermann, Jürgen Adamy:
Gradient Play in $n$-Cluster Games with Zero-Order Information. CoRR abs/2107.12648 (2021) - 2020
- [j6]Tatiana Tatarenko:
Schnelle, verteilte Optimierungsmethoden und spieltheoretische Ansätze in vernetzten Systemen. Autom. 68(3): 166-175 (2020) - [c16]Angelia Nedic, Tatiana Tatarenko:
Convergence Rate of a Penalty Method for Strongly Convex Problems with Linear Constraints. CDC 2020: 372-377 - [c15]Jan Zimmermann, Tatiana Tatarenko, Volker Willert, Jürgen Adamy:
Projected Push-Sum Gradient Descent-Ascent for Convex Optimization with Application to Economic Dispatch Problems. CDC 2020: 542-547 - [i4]Jan Zimmermann, Tatiana Tatarenko, Volker Willert, Jürgen Adamy:
Projected Push-Sum Gradient Descent-Ascent for Convex Optimizationwith Application to Economic Dispatch Problems. CoRR abs/2004.02854 (2020) - [i3]Jan Zimmermann, Tatiana Tatarenko, Volker Willert, Jürgen Adamy:
Revisiting Consensus-Based Energy-Management in Smart Grid with Transmission Losses and Directed Communication. CoRR abs/2009.08758 (2020)
2010 – 2019
- 2019
- [j5]Jan Zimmermann, Tatiana Tatarenko, Volker Willert, Jürgen Adamy:
Optimales Energie-Management über verteilte, beschränkte Gradientenverfahren. Autom. 67(11): 922-935 (2019) - [j4]Tatiana Tatarenko:
Stochastic learning in multi-agent optimization: Communication and payoff-based approaches. Autom. 99: 1-12 (2019) - [j3]Tatiana Tatarenko, Maryam Kamgarpour:
Learning Generalized Nash Equilibria in a Class of Convex Games. IEEE Trans. Autom. Control. 64(4): 1426-1439 (2019) - [c14]Tatiana Tatarenko, Maryam Kamgarpour:
Learning Nash Equilibria in Monotone Games. CDC 2019: 3104-3109 - [c13]Tatiana Tatarenko, Jan Zimmermann, Volker Willert, Jürgen Adamy:
Penalized Push-Sum Algorithm for Constrained Distributed Optimization with Application to Energy Management in Smart Grid. CDC 2019: 6234-6241 - [i2]Tatiana Tatarenko, Maryam Kamgarpour:
Learning Nash Equilibria in Monotone Games. CoRR abs/1904.01882 (2019) - 2018
- [j2]Tatiana Tatarenko:
Independent Log-Linear Learning in Potential Games With Continuous Actions. IEEE Trans. Control. Netw. Syst. 5(3): 913-923 (2018) - [c12]Tatiana Tatarenko, Wei Shi, Angelia Nedic:
Accelerated Gradient Play Algorithm for Distributed Nash Equilibrium Seeking. CDC 2018: 3561-3566 - [c11]Tatiana Tatarenko, Maryam Kamgarpour:
Minimizing Regret in Unconstrained Online Convex Optimization. ECC 2018: 143-148 - [i1]Tatiana Tatarenko, Maryam Kamgarpour:
Minimizing Regret in Bandit Online Optimization in Unconstrained and Constrained Action Spaces. CoRR abs/1806.05069 (2018) - 2017
- [b1]Tatiana Tatarenko:
Game-theoretic learning and distributed optimization in memoryless multi-agent systems. Darmstadt University of Technology, Germany, 2017, pp. 1-169 - [j1]Tatiana Tatarenko, Behrouz Touri:
Non-Convex Distributed Optimization. IEEE Trans. Autom. Control. 62(8): 3744-3757 (2017) - [c10]Angelia Nedic, Tatiana Tatarenko:
On stochastic proximal-point method for convex-composite optimization. Allerton 2017: 198-203 - 2016
- [c9]Tatiana Tatarenko, Behrouz Touri:
On local analysis of distributed optimization. ACC 2016: 5626-5631 - [c8]Tatiana Tatarenko:
Stochastic payoff-based learning in multi-agent systems modeled by means of potential games. CDC 2016: 5298-5303 - [c7]Tatiana Tatarenko:
Stochastic stability of potential function maximizers in continuous version of independent log-linear learning. ECC 2016: 210-215 - 2015
- [c6]Tatiana Tatarenko:
1-recall reinforcement learning leading to an optimal equilibrium in potential games with discrete and continuous actions. CDC 2015: 6749-6754 - [c5]Tatiana Tatarenko:
Synchronous learning of efficient Nash equilibria in potential games with uncoupled dynamics and memoryless players. ECC 2015: 3334-3339 - 2014
- [c4]Tatiana Tatarenko:
Proving convergence of log-linear learning in potential games. ACC 2014: 972-977 - [c3]Tatiana Tatarenko:
Log-linear learning: Convergence in discrete and continuous strategy potential games. CDC 2014: 426-432 - [c2]Tatiana Tatarenko, Luis Garcia-Moreno:
A game theoretic and control theoretic approach to incentive-based demand management in smart grids. MED 2014: 634-639 - [c1]Tatiana Tatarenko:
Finite-time behavior of log-linear learning in potential games. NetGCooP 2014: 158-159
Coauthor Index
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last updated on 2024-07-31 21:41 CEST by the dblp team
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