Anas Barakat
Anas Barakat
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Anas Barakat
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A Prospect-Theoretic Policy Gradient Framework for Behaviorally Nuanced Reinforcement Learning
On the Global Optimality of Policy Gradient Methods in General Utility Reinforcement Learning
Online Multi-Agent Control with Adversarial Disturbances
Optimistic Online Learning in Symmetric Cone Games
Learning Zero-Sum Linear Quadratic Games with Improved Sample Complexity and Last Iterate Convergence
Policy Mirror Descent with Lookahead
Independent Learning in Constrained Markov Potential Games
Learning Zero-Sum Linear Quadratic Games with Improved Sample Complexity
Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space
Stochastic Policy Gradient Methods: Improved Sample Complexity for Fisher-non-degenerate Policies
Analysis of a Target-Based Actor-Critic Algorithm with Linear Function Approximation
Contributions to non-convex stochastic optimization and reinforcement learning
Stochastic optimization with momentum: convergence, fluctuations, and traps avoidance
Convergence and Dynamical Behavior of the ADAM Algorithm for Non-Convex Stochastic Optimization
Convergence Rates of a Momentum Algorithm with Bounded Adaptive Step Size for Non-Convex Optimization
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