Convergence of the ADAM algorithm from a Dynamical System Viewpoint. - Anas Barakat; Pascal Bianchi (CoRR, 2018)

Convergence Analysis of a Momentum Algorithm with Adaptive Step Size for Non Convex Optimization. - Anas Barakat; Pascal Bianchi (CoRR, 2019)

Convergence Rates of a Momentum Algorithm with Bounded Adaptive Step Size for Nonconvex Optimization. - Anas Barakat; Pascal Bianchi (ACML, 2020)

Convergence and Dynamical Behavior of the ADAM Algorithm for Nonconvex Stochastic Optimization. - Anas Barakat; Pascal Bianchi (SIAM J. Optim., 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 (2021)

Analysis of a Target-Based Actor-Critic Algorithm with Linear Function Approximation. - Anas Barakat; Pascal Bianchi; Julien Lehmann (AISTATS, 2022)

Learning Zero-Sum Linear Quadratic Games with Improved Sample Complexity. - Jiduan Wu; Anas Barakat; Ilyas Fatkhullin; Niao He (CDC, 2023)

Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space. - Anas Barakat; Ilyas Fatkhullin; Niao He (ICML, 2023)

Stochastic Policy Gradient Methods: Improved Sample Complexity for Fisher-non-degenerate Policies. - Ilyas Fatkhullin; Anas Barakat; Anastasia Kireeva; Niao He (ICML, 2023)

Independent Learning in Constrained Markov Potential Games. - Philip Jordan; Anas Barakat; Niao He (AISTATS, 2024)

Independent Policy Mirror Descent for Markov Potential Games: Scaling to Large Number of Players. - Pragnya Alatur; Anas Barakat; Niao He (CDC, 2024)

Policy Mirror Descent with Lookahead. - Kimon Protopapas; Anas Barakat (NeurIPS, 2024)

Beyond Expected Returns: A Policy Gradient Algorithm for Cumulative Prospect Theoretic Reinforcement Learning. - Olivier Lepel; Anas Barakat (CoRR, 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)

Optimistic Online Learning in Symmetric Cone Games. - Anas Barakat; Wayne Lin; John Lazarsfeld; Antonios Varvitsiotis (CoRR, 2025)

Multi-Agent Online Control with Adversarial Disturbances. - Anas Barakat; John Lazarsfeld; Georgios Piliouras; Antonios Varvitsiotis (CoRR, 2025)