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Policy Gradient Methods

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Showing 51–100 of 382 papers

TitleStatusHype
Residual Policy Gradient: A Reward View of KL-regularized Objective—0
ROCM: RLHF on consistency models—0
Convergence Guarantees of Model-free Policy Gradient Methods for LQR with Stochastic DataCode0
SPPD: Self-training with Process Preference Learning Using Dynamic Value Margin—0
A Self-Supervised Reinforcement Learning Approach for Fine-Tuning Large Language Models Using Cross-Attention Signals—0
Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and Distillation—0
Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications—0
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement LearningCode0
Self-Interested Agents in Collaborative Learning: An Incentivized Adaptive Data-Centric Framework—0
Reinforcement Learning: An OverviewCode0
BOTS: Batch Bayesian Optimization of Extended Thompson Sampling for Severely Episode-Limited RL Settings—0
Solving Rubik's Cube Without Tricky Sampling—0
Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning—0
Policy Gradient for Robust Markov Decision ProcessesCode0
Truncating Trajectories in Monte Carlo Policy Evaluation: an Adaptive Approach—0
Learning in complex action spaces without policy gradients—0
Strongly-polynomial time and validation analysis of policy gradient methods—0
Landscape of Policy Optimization for Finite Horizon MDPs with General State and Action—0
Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph FormCode0
Reinforcement Learning for Causal Discovery without Acyclicity Constraints—0
Deterministic Policy Gradient Primal-Dual Methods for Continuous-Space Constrained MDPs—0
From Imitation to Refinement -- Residual RL for Precise Assembly—0
PG-Rainbow: Using Distributional Reinforcement Learning in Policy Gradient Methods—0
Towards Adapting Reinforcement Learning Agents to New Tasks: Insights from Q-Values—0
Augmented Bayesian Policy Search—0
Improving Reward-Conditioned Policies for Multi-Armed Bandits using Normalized Weight Functions—0
Current applications and potential future directions of reinforcement learning-based Digital Twins in agriculture—0
Optimal Rates of Convergence for Entropy Regularization in Discounted Markov Decision Processes—0
Entropy annealing for policy mirror descent in continuous time and space—0
Mollification Effects of Policy Gradient Methods—0
Matrix Low-Rank Approximation For Policy Gradient MethodsCode0
Linear Function Approximation as a Computationally Efficient Method to Solve Classical Reinforcement Learning Challenges—0
Policy Gradient Methods for Risk-Sensitive Distributional Reinforcement Learning with Provable Convergence—0
Almost sure convergence rates of stochastic gradient methods under gradient domination—0
An Initial Introduction to Cooperative Multi-Agent Reinforcement Learning—0
Federated Reinforcement Learning with Constraint Heterogeneity—0
Off-OAB: Off-Policy Policy Gradient Method with Optimal Action-Dependent Baseline—0
Information-Theoretic Opacity-Enforcement in Markov Decision Processes—0
Control randomisation approach for policy gradient and application to reinforcement learning in optimal switching—0
Actor-Critic Reinforcement Learning with Phased Actor—0
Intervention-Assisted Policy Gradient Methods for Online Stochastic Queuing Network Optimization: Technical Report—0
Elementary Analysis of Policy Gradient Methods—0
ReAct Meets ActRe: When Language Agents Enjoy Training Data Autonomy—0
Towards Global Optimality for Practical Average Reward Reinforcement Learning without Mixing Time Oracles—0
Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries—0
Towards Efficient Risk-Sensitive Policy Gradient: An Iteration Complexity Analysis—0
Provable Policy Gradient Methods for Average-Reward Markov Potential Games—0
Fill-and-Spill: Deep Reinforcement Learning Policy Gradient Methods for Reservoir Operation Decision and Control—0
Stabilizing Policy Gradients for Stochastic Differential Equations via Consistency with Perturbation Process—0
Towards Provable Log Density Policy Gradient—0
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