Policy Learning
2,633 papers
Papers per year
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12
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14
10
24
16
26
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25
27
61
122
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346
433
377
62
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Papers
Learning to Open and Traverse Doors with a Legged Manipulator
CoRL 2024
Lessons from Learning to Spin “Pens”
CoRL 2024
Linear Alignment: A Closed-form Solution for Aligning Human Preferences without Tuning and Feedback
ICML 2024
Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs
NeurIPS 2024
Low-Rank Bandits via Tight Two-to-Infinity Singular Subspace Recovery
ICML 2024
Low-rank MDPs with Continuous Action Spaces
AISTATS 2024
MaIL: Improving Imitation Learning with Selective State Space Models
CoRL 2024
ManiWAV: Learning Robot Manipulation from In-the-Wild Audio-Visual Data
CoRL 2024
Matryoshka Policy Gradient for Entropy-Regularized RL: Convergence and Global Optimality
JMLR 2024
Maximum entropy GFlowNets with soft Q-learning
AISTATS 2024
Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow
NeurIPS 2024
Mean Field Langevin Actor-Critic: Faster Convergence and Global Optimality beyond Lazy Learning
ICML 2024
Measuring Mutual Policy Divergence for Multi-Agent Sequential Exploration
NeurIPS 2024
Meta-Evolve: Continuous Robot Evolution for One-to-many Policy Transfer
ICLR 2024
Meta Inverse Constrained Reinforcement Learning: Convergence Guarantee and Generalization Analysis
ICLR 2024
Meta-Inverse Reinforcement Learning for Mean Field Games via Probabilistic Context Variables
AAAI 2024
Meta-learning linear quadratic regulators: a policy gradient MAML approach for model-free LQR
L4DC 2024
Meta-Reinforcement Learning with Universal Policy Adaptation: Provable Near-Optimality under All-task Optimum Comparator
NeurIPS 2024
MimicTouch: Leveraging Multi-modal Human Tactile Demonstrations for Contact-rich Manipulation
CoRL 2024
Minimax-optimal reward-agnostic exploration in reinforcement learning
COLT 2024
Mitigating Open-Vocabulary Caption Hallucinations
EMNLP 2024
Mitigating Reward Overoptimization via Lightweight Uncertainty Estimation
NeurIPS 2024
Model-Based Transfer Learning for Contextual Reinforcement Learning
NeurIPS 2024
Model-free Low-Rank Reinforcement Learning via Leveraged Entry-wise Matrix Estimation
NeurIPS 2024
Model-Free Robust $φ$-Divergence Reinforcement Learning Using Both Offline and Online Data
ICML 2024