Research map / Reinforcement learning / Policy gradient and actor-critic
Off-Policy Learning in Large Action Spaces: Optimization Matters More Than Estimation
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- POTEC: Off-Policy Contextual Bandits for Large Action Spaces via Policy Decomposition (ICLR 2025 · similarity 0.92)
- Off-Policy Evaluation for Large Action Spaces via Conjunct Effect Modeling (ICML 2023 · similarity 0.92)
- Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization (ICLR 2022 · similarity 0.92)
- Cross-Domain Off-Policy Evaluation and Learning for Contextual Bandits (ICLR 2025 · similarity 0.90)
- Model Selection for Off-policy Evaluation: New Algorithms and Experimental Protocol (NeurIPS 2025 · similarity 0.90)
- A General Framework for Off-Policy Learning with Partially-Observed Reward (ICLR 2025 · similarity 0.89)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.