Jinglin Chen | DeepAI

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∙ 02/04/2023

Reinforcement Learning in Low-Rank MDPs with Density Features

MDPs with low-rank transitions – that is, the transition matrix can be f...

0 Audrey Huang, et al. ∙

∙ 06/21/2022

On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL

We study reward-free reinforcement learning (RL) under general non-linea...

0 Jinglin Chen, et al. ∙

∙ 03/25/2022

Offline Reinforcement Learning Under Value and Density-Ratio Realizability: the Power of Gaps

We consider a challenging theoretical problem in offline reinforcement l...

0 Jinglin Chen, et al. ∙

∙ 02/14/2022

Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality

Deployment efficiency is an important criterion for many real-world appl...

0 Jiawei Huang, et al. ∙

∙ 02/14/2021

Model-free Representation Learning and Exploration in Low-rank MDPs

The low rank MDP has emerged as an important model for studying represen...

0 Aditya Modi, et al. ∙

∙ 10/23/2020

Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration

This paper studies regret minimization with randomized value functions i...

0 Priyank Agrawal, et al. ∙

∙ 10/08/2020

Nonstationary Reinforcement Learning with Linear Function Approximation

We consider reinforcement learning (RL) in episodic Markov decision proc...

0 Huozhi Zhou, et al. ∙

∙ 07/04/2020

Accelerating Nonconvex Learning via Replica Exchange Langevin Diffusion

Langevin diffusion is a powerful method for nonconvex optimization, whic...

0 Yi Chen, et al. ∙

∙ 05/01/2019

Information-Theoretic Considerations in Batch Reinforcement Learning

Value-function approximation methods that operate in batch mode have fou...

0 Jinglin Chen, et al. ∙

∙ 10/28/2017

Efficient Localized Inference for Large Graphical Models

We propose a new localized inference algorithm for answering marginaliza...

0 Jinglin Chen, et al. ∙

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