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Reinforcement Learning
2932 directly classified papers
Papers per year
2003: 1
2006: 11
2007: 18
2008: 23
2009: 14
2010: 22
2011: 24
2012: 34
2013: 26
2014: 24
2015: 14
2016: 23
2017: 79
2018: 182
2019: 255
2020: 284
2021: 333
2022: 319
2023: 315
2024: 457
2025: 419
2026: 55
Papers
RGMDT: Return-Gap-Minimizing Decision Tree Extraction in Non-Euclidean Metric Space
NIPS 2024
BoNBoN Alignment for Large Language Models and the Sweetness of Best-of-n Sampling
NIPS 2024
Policy Learning from Tutorial Books via Understanding, Rehearsing and Introspecting
NIPS 2024
Graph Diffusion Policy Optimization
NIPS 2024
Causal Imitation for Markov Decision Processes: a Partial Identification Approach
NIPS 2024
Implicit Curriculum in Procgen Made Explicit
NIPS 2024
AlphaMath Almost Zero: Process Supervision without Process
NIPS 2024
Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning
NIPS 2024
Doubly Mild Generalization for Offline Reinforcement Learning
NIPS 2024
Online Control with Adversarial Disturbance for Continuous-time Linear Systems
NIPS 2024
REBEL: Reinforcement Learning via Regressing Relative Rewards
NIPS 2024
Amortized Active Causal Induction with Deep Reinforcement Learning
NIPS 2024
Goal-Conditioned On-Policy Reinforcement Learning
NIPS 2024
Learning Successor Features the Simple Way
NIPS 2024
DiffPhyCon: A Generative Approach to Control Complex Physical Systems
NIPS 2024
Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning
NIPS 2024
Robust Reinforcement Learning with General Utility
NIPS 2024
Perplexity-aware Correction for Robust Alignment with Noisy Preferences
NIPS 2024
Policy Optimization for Robust Average Reward MDPs
NIPS 2024
A2PO: Towards Effective Offline Reinforcement Learning from an Advantage-aware Perspective
NIPS 2024
Enhancing Robustness of Graph Neural Networks on Social Media with Explainable Inverse Reinforcement Learning
NIPS 2024
Statistical Efficiency of Distributional Temporal Difference Learning
NIPS 2024
Controlled maximal variability along with reliable performance in recurrent neural networks
NIPS 2024
Reinforcement Learning with Adaptive Regularization for Safe Control of Critical Systems
NIPS 2024
Predicting Future Actions of Reinforcement Learning Agents
NIPS 2024
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