Research map / Reinforcement learning / Policy gradient and actor-critic
Subgaussian and Differentiable Importance Sampling for Off-Policy Evaluation and Learning
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Closest papers by meaning
- From Importance Sampling to Doubly Robust Policy Gradient (ICML 2020 · similarity 0.90)
- Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning (NeurIPS 2019 · similarity 0.90)
- Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning (NeurIPS 2024 · similarity 0.90)
- Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation (NeurIPS 2018 · similarity 0.90)
- Importance Sampling Policy Evaluation with an Estimated Behavior Policy (ICML 2019 · similarity 0.90)
- Demystifying the Paradox of Importance Sampling with an Estimated History-Dependent Behavior Policy in Off-Policy Evaluation (ICML 2025 · similarity 0.88)
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