Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model
Fuente:
arXiv
Saved in:
| Main Authors: | Li, Gen, Wei, Yuting, Chi, Yuejie, Chen, Yuxin |
|---|---|
| Format: | Preprint |
| Published: |
2020
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis
by: Li, Gen, et al.
Published: (2021)
by: Li, Gen, et al.
Published: (2021)
Settling the Sample Complexity of Model-Based Offline Reinforcement Learning
by: Li, Gen, et al.
Published: (2022)
by: Li, Gen, et al.
Published: (2022)
Statistical and Algorithmic Foundations of Reinforcement Learning
by: Chi, Yuejie, et al.
Published: (2025)
by: Chi, Yuejie, et al.
Published: (2025)
High-probability sample complexities for policy evaluation with linear function approximation
by: Li, Gen, et al.
Published: (2023)
by: Li, Gen, et al.
Published: (2023)
Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models
by: Li, Gen, et al.
Published: (2023)
by: Li, Gen, et al.
Published: (2023)
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model
by: Shi, Laixi, et al.
Published: (2023)
by: Shi, Laixi, et al.
Published: (2023)
Accelerating Convergence of Score-Based Diffusion Models, Provably
by: Li, Gen, et al.
Published: (2024)
by: Li, Gen, et al.
Published: (2024)
Minimax-Optimal Reward-Agnostic Exploration in Reinforcement Learning
by: Li, Gen, et al.
Published: (2023)
by: Li, Gen, et al.
Published: (2023)
Fast Computation of Optimal Transport via Entropy-Regularized Extragradient Methods
by: Li, Gen, et al.
Published: (2023)
by: Li, Gen, et al.
Published: (2023)
Non-convex matrix sensing: Breaking the quadratic rank barrier in the sample complexity
by: Stöger, Dominik, et al.
Published: (2024)
by: Stöger, Dominik, et al.
Published: (2024)
Optimal transport natural gradient for statistical manifolds with continuous sample space
by: Chen, Yifan, et al.
Published: (2018)
by: Chen, Yifan, et al.
Published: (2018)
In-Context Learning with Representations: Contextual Generalization of Trained Transformers
by: Yang, Tong, et al.
Published: (2024)
by: Yang, Tong, et al.
Published: (2024)
Breaking AR's Sampling Bottleneck: Provable Acceleration via Diffusion Language Models
by: Li, Gen, et al.
Published: (2025)
by: Li, Gen, et al.
Published: (2025)
A Sharp Convergence Theory for The Probability Flow ODEs of Diffusion Models
by: Li, Gen, et al.
Published: (2024)
by: Li, Gen, et al.
Published: (2024)
Model-Based Reinforcement Learning for Offline Zero-Sum Markov Games
by: Yan, Yuling, et al.
Published: (2022)
by: Yan, Yuling, et al.
Published: (2022)
The Local Landscape of Phase Retrieval Under Limited Samples
by: Liu, Kaizhao, et al.
Published: (2023)
by: Liu, Kaizhao, et al.
Published: (2023)
Long-time dynamics and universality of nonconvex gradient descent
by: Han, Qiyang
Published: (2025)
by: Han, Qiyang
Published: (2025)
Mixing Time of the Proximal Sampler in Relative Fisher Information via Strong Data Processing Inequality
by: Wibisono, Andre
Published: (2025)
by: Wibisono, Andre
Published: (2025)
A Theory of Feature Learning in Kernel Models
by: Chen, Yunlu, et al.
Published: (2023)
by: Chen, Yunlu, et al.
Published: (2023)
Multi-head Transformers Provably Learn Symbolic Multi-step Reasoning via Gradient Descent
by: Yang, Tong, et al.
Published: (2025)
by: Yang, Tong, et al.
Published: (2025)
Robustly Learning Monotone Generalized Linear Models via Data Augmentation
by: Zarifis, Nikos, et al.
Published: (2025)
by: Zarifis, Nikos, et al.
Published: (2025)
Breaking the Finite-Sample Barrier in Entropy Coupling
by: Asoodeh, Shahab, et al.
Published: (2026)
by: Asoodeh, Shahab, et al.
Published: (2026)
Ensemble-Conditional Gaussian Processes (Ens-CGP): Representation, Geometry, and Inference
by: Ravela, Sai, et al.
Published: (2026)
by: Ravela, Sai, et al.
Published: (2026)
Gradient descent inference in empirical risk minimization
by: Han, Qiyang, et al.
Published: (2024)
by: Han, Qiyang, et al.
Published: (2024)
Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs
by: Zurek, Matthew, et al.
Published: (2024)
by: Zurek, Matthew, et al.
Published: (2024)
Quickest Change Detection with Confusing Change
by: Chen, Yu-Zhen Janice, et al.
Published: (2024)
by: Chen, Yu-Zhen Janice, et al.
Published: (2024)
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning
by: Zhang, Dake, et al.
Published: (2024)
by: Zhang, Dake, et al.
Published: (2024)
Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems
by: Puchkin, Nikita, et al.
Published: (2023)
by: Puchkin, Nikita, et al.
Published: (2023)
On the Sample Complexity of Set Membership Estimation for Linear Systems with Disturbances Bounded by Convex Sets
by: Xu, Haonan, et al.
Published: (2024)
by: Xu, Haonan, et al.
Published: (2024)
Towards a mathematical theory for consistency training in diffusion models
by: Li, Gen, et al.
Published: (2024)
by: Li, Gen, et al.
Published: (2024)
Span-Based Optimal Sample Complexity for Average Reward MDPs
by: Zurek, Matthew, et al.
Published: (2023)
by: Zurek, Matthew, et al.
Published: (2023)
Stochastic Optimization with Optimal Importance Sampling
by: Aolaritei, Liviu, et al.
Published: (2025)
by: Aolaritei, Liviu, et al.
Published: (2025)
A non-asymptotic distributional theory of approximate message passing for sparse and robust regression
by: Li, Gen, et al.
Published: (2024)
by: Li, Gen, et al.
Published: (2024)
Efficient Sampling with Discrete Diffusion Models: Sharp and Adaptive Guarantees
by: Dmitriev, Daniil, et al.
Published: (2026)
by: Dmitriev, Daniil, et al.
Published: (2026)
Frequentist Regret Analysis of Gaussian Process Thompson Sampling via Fractional Posteriors
by: Roy, Somjit, et al.
Published: (2026)
by: Roy, Somjit, et al.
Published: (2026)
An Improved Analysis of Langevin Algorithms with Prior Diffusion for Non-Log-Concave Sampling
by: Huang, Xunpeng, et al.
Published: (2024)
by: Huang, Xunpeng, et al.
Published: (2024)
Variational Transport: A Convergent Particle-BasedAlgorithm for Distributional Optimization
by: Yang, Zhuoran, et al.
Published: (2020)
by: Yang, Zhuoran, et al.
Published: (2020)
Beyond Maximum Likelihood: Variational Inequality Estimation for Generalized Linear Models
by: Zhu, Linglingzhi, et al.
Published: (2025)
by: Zhu, Linglingzhi, et al.
Published: (2025)
Kernel Mean Embedding Topology: Weak and Strong Forms for Stochastic Kernels and Implications for Model Learning
by: Saldi, Naci, et al.
Published: (2025)
by: Saldi, Naci, et al.
Published: (2025)
Learning the Uncertainty Sets for Control Dynamics via Set Membership: A Non-Asymptotic Analysis
by: Li, Yingying, et al.
Published: (2023)
by: Li, Yingying, et al.
Published: (2023)
Similar Items
-
Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis
by: Li, Gen, et al.
Published: (2021) -
Settling the Sample Complexity of Model-Based Offline Reinforcement Learning
by: Li, Gen, et al.
Published: (2022) -
Statistical and Algorithmic Foundations of Reinforcement Learning
by: Chi, Yuejie, et al.
Published: (2025) -
High-probability sample complexities for policy evaluation with linear function approximation
by: Li, Gen, et al.
Published: (2023) -
Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models
by: Li, Gen, et al.
Published: (2023)