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Policy Gradient Methods

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Showing 101–150 of 382 papers

TitleStatusHype
Reusing Historical Trajectories in Natural Policy Gradient via Importance Sampling: Convergence and Convergence Rate—0
When Do Off-Policy and On-Policy Policy Gradient Methods Align?—0
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
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Methods—0
Global Convergence of Policy Gradient Methods in Reinforcement Learning, Games and Control—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
Learning Decentralized Partially Observable Mean Field Control for Artificial Collective Behavior—0
Provably Convergent Policy Optimization via Metric-aware Trust Region Methods—0
Correcting discount-factor mismatch in on-policy policy gradient methods—0
Acceleration in Policy Optimization—0
Deep Policy Gradient Methods in Commodity Markets—0
Stepsize Learning for Policy Gradient Methods in Contextual Markov Decision Processes—0
Confidence-Controlled Exploration: Efficient Sparse-Reward Policy Learning for Robot Navigation—0
Solving Robust MDPs through No-Regret Dynamics—0
Adaptive Policy Learning to Additional Tasks—0
Shattering the Agent-Environment Interface for Fine-Tuning Inclusive Language Models—0
Client Selection for Federated Policy Optimization with Environment HeterogeneityCode0
Policy Gradient Methods for Discrete Time Linear Quadratic Regulator With Random Parameters—0
Policy Mirror Descent Inherently Explores Action Space—0
Policy gradient learning methods for stochastic control with exit time and applications to share repurchase pricing—0
A Policy Gradient Framework for Stochastic Optimal Control Problems with Global Convergence Guarantee—0
Distributional constrained reinforcement learning for supply chain optimizationCode0
Stochastic Policy Gradient Methods: Improved Sample Complexity for Fisher-non-degenerate Policies—0
Accelerating Policy Gradient by Estimating Value Function from Prior Computation in Deep Reinforcement Learning—0
Policy Gradient for Rectangular Robust Markov Decision Processes—0
SoftTreeMax: Exponential Variance Reduction in Policy Gradient via Tree Search—0
Stochastic Dimension-reduced Second-order Methods for Policy Optimization—0
On the Global Convergence of Risk-Averse Policy Gradient Methods with Expected Conditional Risk Measures—0
On the Convergence of Discounted Policy Gradient Methods—0
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