Tatiana Tatarenko

Orcid: 0000-0001-8951-112X

According to our database1, Tatiana Tatarenko authored at least 35 papers between 2014 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2022
Projected gradient-tracking in multi-cluster games and its application to power management.
CoRR, 2022

On the Rate of Convergence of Payoff-based Algorithms to Nash Equilibrium in Strongly Monotone Games.
CoRR, 2022

Gradient-Tracking-basierte Lösung von Multi-Cluster-Spielen.
Autom., 2022

Distributed optimization methods for N-cluster games.
Autom., 2022

2021
Geometric Convergence of Gradient Play Algorithms for Distributed Nash Equilibrium Seeking.
IEEE Trans. Autom. Control., 2021

A Smooth Inexact Penalty Reformulation of Convex Problems with Linear Constraints.
SIAM J. Optim., 2021

Solving leaderless multi-cluster games over directed graphs.
Eur. J. Control, 2021

Gradient-Tracking over Directed Graphs for solving Leaderless Multi-Cluster Games.
CoRR, 2021

Gradient Play in n-Cluster Games with Zero-Order Information.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020
Revisiting Consensus-Based Energy-Management in Smart Grid with Transmission Losses and Directed Communication.
CoRR, 2020

Projected Push-Sum Gradient Descent-Ascent for Convex Optimizationwith Application to Economic Dispatch Problems.
CoRR, 2020

Schnelle, verteilte Optimierungsmethoden und spieltheoretische Ansätze in vernetzten Systemen.
Autom., 2020

Projected Push-Sum Gradient Descent-Ascent for Convex Optimization with Application to Economic Dispatch Problems.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Convergence Rate of a Penalty Method for Strongly Convex Problems with Linear Constraints.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020

2019
Learning Generalized Nash Equilibria in a Class of Convex Games.
IEEE Trans. Autom. Control., 2019

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

Optimales Energie-Management über verteilte, beschränkte Gradientenverfahren.
Autom., 2019

Penalized Push-Sum Algorithm for Constrained Distributed Optimization with Application to Energy Management in Smart Grid.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Learning Nash Equilibria in Monotone Games.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

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

Minimizing Regret in Bandit Online Optimization in Unconstrained and Constrained Action Spaces.
CoRR, 2018

Minimizing Regret in Unconstrained Online Convex Optimization.
Proceedings of the 16th European Control Conference, 2018

Accelerated Gradient Play Algorithm for Distributed Nash Equilibrium Seeking.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017
Game-theoretic learning and distributed optimization in memoryless multi-agent systems.
PhD thesis, 2017

Non-Convex Distributed Optimization.
IEEE Trans. Autom. Control., 2017

On stochastic proximal-point method for convex-composite optimization.
Proceedings of the 55th Annual Allerton Conference on Communication, 2017

2016
Stochastic stability of potential function maximizers in continuous version of independent log-linear learning.
Proceedings of the 15th European Control Conference, 2016

Stochastic payoff-based learning in multi-agent systems modeled by means of potential games.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

On local analysis of distributed optimization.
Proceedings of the 2016 American Control Conference, 2016

2015
Synchronous learning of efficient Nash equilibria in potential games with uncoupled dynamics and memoryless players.
Proceedings of the 14th European Control Conference, 2015

1-recall reinforcement learning leading to an optimal equilibrium in potential games with discrete and continuous actions.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

2014
Finite-time behavior of log-linear learning in potential games.
Proceedings of the 7th International Conference on NETwork Games, COntrol and OPtimization, 2014

A game theoretic and control theoretic approach to incentive-based demand management in smart grids.
Proceedings of the 22nd Mediterranean Conference on Control and Automation, 2014

Log-linear learning: Convergence in discrete and continuous strategy potential games.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

Proving convergence of log-linear learning in potential games.
Proceedings of the American Control Conference, 2014


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