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Policy Gradient Methods

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TitleStatusHype
Statistically Efficient Off-Policy Policy Gradients—0
Stein Variational Policy Gradient—0
Stepsize Learning for Policy Gradient Methods in Contextual Markov Decision Processes—0
Stochastic Dimension-reduced Second-order Methods for Policy Optimization—0
Stochastic first-order methods for average-reward Markov decision processes—0
Stochastic Policy Gradient Methods: Improved Sample Complexity for Fisher-non-degenerate Policies—0
Stochastic Recursive Momentum for Policy Gradient Methods—0
Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function—0
Stochastic Variance Reduction for Policy Gradient Estimation—0
Strategic bidding in freight transport using deep reinforcement learning—0
Strongly-polynomial time and validation analysis of policy gradient methods—0
Symmetric (Optimistic) Natural Policy Gradient for Multi-agent Learning with Parameter Convergence—0
Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning—0
Theoretical Guarantees of Fictitious Discount Algorithms for Episodic Reinforcement Learning and Global Convergence of Policy Gradient Methods—0
The wisdom of the crowd: reliable deep reinforcement learning through ensembles of Q-functions—0
Token-Efficient RL for LLM Reasoning—0
Towards Adapting Reinforcement Learning Agents to New Tasks: Insights from Q-Values—0
Towards Efficient Risk-Sensitive Policy Gradient: An Iteration Complexity Analysis—0
Towards Global Optimality in Cooperative MARL with the Transformation And Distillation Framework—0
Towards Provable Log Density Policy Gradient—0
Training Diffusion Models Towards Diverse Image Generation with Reinforcement Learning—0
Trajectory-wise Control Variates for Variance Reduction in Policy Gradient Methods—0
Transfer Reward Learning for Policy Gradient-Based Text Generation—0
Truncating Trajectories in Monte Carlo Policy Evaluation: an Adaptive Approach—0
Policy Gradient in Partially Observable Environments: Approximation and Convergence—0
Understanding Early Word Learning in Situated Artificial Agents—0
Understanding Grounded Language Learning Agents—0
Value-Based Reinforcement Learning for Continuous Control Robotic Manipulation in Multi-Task Sparse Reward Settings—0
Variance Reduced Domain Randomization for Policy Gradient—0
Variance Reduction for Policy-Gradient Methods via Empirical Variance Minimization—0
Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines—0
Variance Reduction for Reinforcement Learning in Input-Driven Environments—0
Variance Reduction in Actor Critic Methods (ACM)—0
When Do Off-Policy and On-Policy Policy Gradient Methods Align?—0
Diversity-Inducing Policy Gradient: Using Maximum Mean Discrepancy to Find a Set of Diverse Policies—0
Fast Global Convergence of Natural Policy Gradient Methods with Entropy Regularization—0
Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning—0
Federated Reinforcement Learning with Constraint Heterogeneity—0
Fill-and-Spill: Deep Reinforcement Learning Policy Gradient Methods for Reservoir Operation Decision and Control—0
Fine-Grained AutoAugmentation for Multi-Label Classification—0
Fingerprint Policy Optimisation for Robust Reinforcement Learning—0
Focused Hierarchical RNNs for Conditional Sequence Processing—0
f-Policy Gradients: A General Framework for Goal Conditioned RL using f-Divergences—0
From Imitation to Refinement -- Residual RL for Precise Assembly—0
GACEM: Generalized Autoregressive Cross Entropy Method for Multi-Modal Black Box Constraint Satisfaction—0
Geometry and convergence of natural policy gradient methods—0
Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries—0
Global Convergence of Natural Policy Gradient with Hessian-aided Momentum Variance Reduction—0
Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator—0
Global Convergence of Policy Gradient Methods for Linearized Control Problems—0
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