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Policy Gradient Methods

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TitleStatusHype
Identifying Policy Gradient Subspaces—0
Global Convergence of Natural Policy Gradient with Hessian-aided Momentum Variance Reduction—0
Training Diffusion Models Towards Diverse Image Generation with Reinforcement Learning—0
Optimistic Policy Gradient in Multi-Player Markov Games with a Single Controller: Convergence Beyond the Minty Property—0
Privacy Preserving Multi-Agent Reinforcement Learning in Supply Chains—0
RL Dreams: Policy Gradient Optimization for Score Distillation based 3D Generation—0
Score-Aware Policy-Gradient Methods and Performance Guarantees using Local Lyapunov Conditions: Applications to Product-Form Stochastic Networks and Queueing Systems—0
Predictable Reinforcement Learning Dynamics through Entropy Rate MinimizationCode0
A Large Deviations Perspective on Policy Gradient Algorithms—0
Clipped-Objective Policy Gradients for Pessimistic Policy OptimizationCode0
On the Second-Order Convergence of Biased Policy Gradient Algorithms—0
Riemannian stochastic optimization methods avoid strict saddle points—0
Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning—0
Optimization Landscape of Policy Gradient Methods for Discrete-time Static Output Feedback—0
Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement LearningCode0
f-Policy Gradients: A General Framework for Goal Conditioned RL using f-Divergences—0
Global Convergence of Policy Gradient Methods in Reinforcement Learning, Games and Control—0
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Methods—0
Beyond Stationarity: Convergence Analysis of Stochastic Softmax Policy Gradient Methods—0
Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds—0
Oracle Complexity Reduction for Model-free LQR: A Stochastic Variance-Reduced Policy Gradient ApproachCode0
Learning Zero-Sum Linear Quadratic Games with Improved Sample Complexity and Last-Iterate ConvergenceCode0
Commodities Trading through Deep Policy Gradient Methods—0
Hindsight-DICE: Stable Credit Assignment for Deep Reinforcement LearningCode0
Enabling Efficient, Reliable Real-World Reinforcement Learning with Approximate Physics-Based ModelsCode0
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