Research map / Learning theory and algorithms / Kernels and regression theory
Understanding and Leveraging Overparameterization in Recursive Value 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
- Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit Parameterization (NeurIPS 2021 · similarity 0.89)
- Stop Regressing: Training Value Functions via Classification for Scalable Deep RL (ICML 2024 · similarity 0.88)
- Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood (ICLR 2025 · similarity 0.87)
- Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation (ICML 2024 · similarity 0.87)
- Neural Network Approximation for Pessimistic Offline Reinforcement Learning (AAAI 2024 · similarity 0.87)
- Enhancing Value Function Estimation through First-Order State-Action Dynamics in Offline Reinforcement Learning (ICML 2024 · similarity 0.87)
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.
