Anas Barakat

According to our database, Anas Barakat authored at least 16 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Multi-Agent Online Control with Adversarial Disturbances.

Anas Barakat, John Lazarsfeld, Georgios Piliouras, Antonios Varvitsiotis

CoRR, June, 2025

Optimistic Online Learning in Symmetric Cone Games.

Anas Barakat, Wayne Lin, John Lazarsfeld, Antonios Varvitsiotis

CoRR, April, 2025

2024

On the Sample Complexity of a Policy Gradient Algorithm with Occupancy Approximation for General Utility Reinforcement Learning.

Anas Barakat, Souradip Chakraborty, Peihong Yu, Pratap Tokekar, Amrit Singh Bedi

CoRR, 2024

Beyond Expected Returns: A Policy Gradient Algorithm for Cumulative Prospect Theoretic Reinforcement Learning.

Olivier Lepel, Anas Barakat

CoRR, 2024

Policy Mirror Descent with Lookahead.

Kimon Protopapas, Anas Barakat

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Independent Policy Mirror Descent for Markov Potential Games: Scaling to Large Number of Players.

Pragnya Alatur, Anas Barakat, Niao He

Proceedings of the 63rd IEEE Conference on Decision and Control, 2024

Independent Learning in Constrained Markov Potential Games.

Philip Jordan, Anas Barakat, Niao He

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Stochastic Policy Gradient Methods: Improved Sample Complexity for Fisher-non-degenerate Policies.

Ilyas Fatkhullin, Anas Barakat, Anastasia Kireeva, Niao He

Proceedings of the International Conference on Machine Learning, 2023

Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space.

Anas Barakat, Ilyas Fatkhullin, Niao He

Proceedings of the International Conference on Machine Learning, 2023

Learning Zero-Sum Linear Quadratic Games with Improved Sample Complexity.

Jiduan Wu, Anas Barakat, Ilyas Fatkhullin, Niao He

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

Analysis of a Target-Based Actor-Critic Algorithm with Linear Function Approximation.

Anas Barakat, Pascal Bianchi, Julien Lehmann

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Contributions to non-convex stochastic optimization and reinforcement learning. (Contributions à l'optimisation stochastique non convexe et à l'apprentissage par renforcement).

Anas Barakat

PhD thesis, 2021

Convergence and Dynamical Behavior of the ADAM Algorithm for Nonconvex Stochastic Optimization.

Anas Barakat, Pascal Bianchi

SIAM J. Optim., 2021

2020

Convergence Rates of a Momentum Algorithm with Bounded Adaptive Step Size for Nonconvex Optimization.

Anas Barakat, Pascal Bianchi

Proceedings of The 12th Asian Conference on Machine Learning, 2020

2019

Convergence Analysis of a Momentum Algorithm with Adaptive Step Size for Non Convex Optimization.

Anas Barakat, Pascal Bianchi

CoRR, 2019

2018

Convergence of the ADAM algorithm from a Dynamical System Viewpoint.

Anas Barakat, Pascal Bianchi

CoRR, 2018