ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2006.11274
  4. Cited By
On Reward-Free Reinforcement Learning with Linear Function Approximation

On Reward-Free Reinforcement Learning with Linear Function Approximation

19 June 2020
Ruosong Wang
S. Du
Lin F. Yang
Ruslan Salakhutdinov
    OffRL
ArXivPDFHTML

Papers citing "On Reward-Free Reinforcement Learning with Linear Function Approximation"

22 / 22 papers shown
Title
From "Thumbs Up" to "10 out of 10": Reconsidering Scalar Feedback in
  Interactive Reinforcement Learning
From "Thumbs Up" to "10 out of 10": Reconsidering Scalar Feedback in Interactive Reinforcement Learning
Hang Yu
Reuben M. Aronson
Katherine H. Allen
E. Short
42
3
0
17 Nov 2023
When is Agnostic Reinforcement Learning Statistically Tractable?
When is Agnostic Reinforcement Learning Statistically Tractable?
Zeyu Jia
Gene Li
Alexander Rakhlin
Ayush Sekhari
Nathan Srebro
OffRL
27
5
0
09 Oct 2023
Policy Finetuning in Reinforcement Learning via Design of Experiments
  using Offline Data
Policy Finetuning in Reinforcement Learning via Design of Experiments using Offline Data
Ruiqi Zhang
Andrea Zanette
OffRL
OnRL
40
7
0
10 Jul 2023
Improved Sample Complexity for Reward-free Reinforcement Learning under
  Low-rank MDPs
Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs
Yuan Cheng
Ruiquan Huang
J. Yang
Yitao Liang
OffRL
41
8
0
20 Mar 2023
Refined Regret for Adversarial MDPs with Linear Function Approximation
Refined Regret for Adversarial MDPs with Linear Function Approximation
Yan Dai
Haipeng Luo
Chen-Yu Wei
Julian Zimmert
25
12
0
30 Jan 2023
Provably Efficient Model-free RL in Leader-Follower MDP with Linear
  Function Approximation
Provably Efficient Model-free RL in Leader-Follower MDP with Linear Function Approximation
A. Ghosh
17
1
0
28 Nov 2022
Learning General World Models in a Handful of Reward-Free Deployments
Learning General World Models in a Handful of Reward-Free Deployments
Yingchen Xu
Jack Parker-Holder
Aldo Pacchiano
Philip J. Ball
Oleh Rybkin
Stephen J. Roberts
Tim Rocktaschel
Edward Grefenstette
OffRL
55
8
0
23 Oct 2022
On the Statistical Efficiency of Reward-Free Exploration in Non-Linear
  RL
On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL
Jinglin Chen
Aditya Modi
A. Krishnamurthy
Nan Jiang
Alekh Agarwal
38
25
0
21 Jun 2022
BYOL-Explore: Exploration by Bootstrapped Prediction
BYOL-Explore: Exploration by Bootstrapped Prediction
Z. Guo
S. Thakoor
Miruna Pislar
Bernardo Avila-Pires
Florent Altché
...
Yunhao Tang
Michal Valko
Rémi Munos
M. G. Azar
Bilal Piot
22
68
0
16 Jun 2022
Provable Benefits of Representational Transfer in Reinforcement Learning
Provable Benefits of Representational Transfer in Reinforcement Learning
Alekh Agarwal
Yuda Song
Wen Sun
Kaiwen Wang
Mengdi Wang
Xuezhou Zhang
OffRL
21
33
0
29 May 2022
Near-optimal Offline Reinforcement Learning with Linear Representation:
  Leveraging Variance Information with Pessimism
Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism
Ming Yin
Yaqi Duan
Mengdi Wang
Yu-Xiang Wang
OffRL
32
65
0
11 Mar 2022
Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement
  Learning
Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning
Chenjia Bai
Lingxiao Wang
Zhuoran Yang
Zhihong Deng
Animesh Garg
Peng Liu
Zhaoran Wang
OffRL
28
132
0
23 Feb 2022
Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost
Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost
Dan Qiao
Ming Yin
Ming Min
Yu-Xiang Wang
31
28
0
13 Feb 2022
Gap-Dependent Unsupervised Exploration for Reinforcement Learning
Gap-Dependent Unsupervised Exploration for Reinforcement Learning
Jingfeng Wu
Vladimir Braverman
Lin F. Yang
24
12
0
11 Aug 2021
Sample-Efficient Reinforcement Learning Is Feasible for Linearly
  Realizable MDPs with Limited Revisiting
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting
Gen Li
Yuxin Chen
Yuejie Chi
Yuantao Gu
Yuting Wei
OffRL
24
28
0
17 May 2021
Optimal Uniform OPE and Model-based Offline Reinforcement Learning in
  Time-Homogeneous, Reward-Free and Task-Agnostic Settings
Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings
Ming Yin
Yu-Xiang Wang
OffRL
32
19
0
13 May 2021
An Exponential Lower Bound for Linearly-Realizable MDPs with Constant
  Suboptimality Gap
An Exponential Lower Bound for Linearly-Realizable MDPs with Constant Suboptimality Gap
Yuanhao Wang
Ruosong Wang
Sham Kakade
OffRL
39
43
0
23 Mar 2021
Improved Variance-Aware Confidence Sets for Linear Bandits and Linear
  Mixture MDP
Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP
Zihan Zhang
Jiaqi Yang
Xiangyang Ji
S. Du
68
36
0
29 Jan 2021
Logistic Q-Learning
Logistic Q-Learning
Joan Bas-Serrano
Sebastian Curi
Andreas Krause
Gergely Neu
9
40
0
21 Oct 2020
A Sharp Analysis of Model-based Reinforcement Learning with Self-Play
A Sharp Analysis of Model-based Reinforcement Learning with Self-Play
Qinghua Liu
Tiancheng Yu
Yu Bai
Chi Jin
29
121
0
04 Oct 2020
Adaptive Reward-Free Exploration
Adaptive Reward-Free Exploration
E. Kaufmann
Pierre Ménard
O. D. Domingues
Anders Jonsson
Edouard Leurent
Michal Valko
27
79
0
11 Jun 2020
Reward-Free Exploration for Reinforcement Learning
Reward-Free Exploration for Reinforcement Learning
Chi Jin
A. Krishnamurthy
Max Simchowitz
Tiancheng Yu
OffRL
112
194
0
07 Feb 2020
1