Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1912.06366
Cited By
v1
v2 (latest)
Provably Efficient Reinforcement Learning with Aggregated States
13 December 2019
Shi Dong
Benjamin Van Roy
Zhengyuan Zhou
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Provably Efficient Reinforcement Learning with Aggregated States"
21 / 21 papers shown
Demystifying Linear MDPs and Novel Dynamics Aggregation Framework
International Conference on Learning Representations (ICLR), 2024
Joongkyu Lee
Min-hwan Oh
339
5
0
31 Oct 2024
The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions
Physical Review X (PRX), 2023
Nishil Patel
Sebastian Lee
Stefano Sarao Mannelli
Sebastian Goldt
Adrew Saxe
OffRL
528
8
0
17 Jun 2023
Exponential Hardness of Reinforcement Learning with Linear Function Approximation
Annual Conference Computational Learning Theory (COLT), 2023
Daniel M. Kane
Sihan Liu
Shachar Lovett
G. Mahajan
Csaba Szepesvári
Gellert Weisz
300
6
0
25 Feb 2023
Tight Guarantees for Interactive Decision Making with the Decision-Estimation Coefficient
Annual Conference Computational Learning Theory (COLT), 2023
Dylan J. Foster
Noah Golowich
Yanjun Han
OffRL
322
30
0
19 Jan 2023
Model-Free Reinforcement Learning with the Decision-Estimation Coefficient
Neural Information Processing Systems (NeurIPS), 2022
Dylan J. Foster
Noah Golowich
Jian Qian
Alexander Rakhlin
Ayush Sekhari
OffRL
291
12
0
25 Nov 2022
Planning to the Information Horizon of BAMDPs via Epistemic State Abstraction
Neural Information Processing Systems (NeurIPS), 2022
Dilip Arumugam
Satinder Singh
238
7
0
30 Oct 2022
A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
International Conference on Learning Representations (ICLR), 2022
Zixiang Chen
C. J. Li
An Yuan
Quanquan Gu
Michael I. Jordan
OffRL
290
30
0
30 Sep 2022
Learning to Order for Inventory Systems with Lost Sales and Uncertain Supplies
Management Sciences (MS), 2022
Boxiao Chen
Jiashuo Jiang
Jiawei Zhang
Zhengyuan Zhou
296
15
0
10 Jul 2022
On the Complexity of Adversarial Decision Making
Neural Information Processing Systems (NeurIPS), 2022
Dylan J. Foster
Alexander Rakhlin
Ayush Sekhari
Karthik Sridharan
AAML
292
32
0
27 Jun 2022
Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning
Neural Information Processing Systems (NeurIPS), 2022
Dilip Arumugam
Benjamin Van Roy
OffRL
395
20
0
04 Jun 2022
Finding Safe Zones of policies Markov Decision Processes
Neural Information Processing Systems (NeurIPS), 2022
Lee Cohen
Yishay Mansour
Michal Moshkovitz
360
1
0
23 Feb 2022
Computational-Statistical Gaps in Reinforcement Learning
D. Kane
Sihan Liu
Shachar Lovett
G. Mahajan
190
5
0
11 Feb 2022
Improved Algorithms for Misspecified Linear Markov Decision Processes
Daniel Vial
Advait Parulekar
Sanjay Shakkottai
R. Srikant
268
7
0
12 Sep 2021
Regret Minimization Experience Replay in Off-Policy Reinforcement Learning
Neural Information Processing Systems (NeurIPS), 2021
Xu-Hui Liu
Zhenghai Xue
Jing-Cheng Pang
Shengyi Jiang
Feng Xu
Yang Yu
OffRL
268
48
0
15 May 2021
Bilinear Classes: A Structural Framework for Provable Generalization in RL
International Conference on Machine Learning (ICML), 2021
S. Du
Sham Kakade
Jason D. Lee
Shachar Lovett
G. Mahajan
Wen Sun
Ruosong Wang
OffRL
607
204
0
19 Mar 2021
Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve Optimism, Embrace Virtual Curvature
Neural Information Processing Systems (NeurIPS), 2021
Kefan Dong
Jiaqi Yang
Tengyu Ma
683
37
0
08 Feb 2021
Randomized Value Functions via Posterior State-Abstraction Sampling
Dilip Arumugam
Benjamin Van Roy
OffRL
349
7
0
05 Oct 2020
Approximation Benefits of Policy Gradient Methods with Aggregated States
Daniel Russo
430
7
0
22 Jul 2020
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning
Neural Information Processing Systems (NeurIPS), 2020
Alekh Agarwal
Mikael Henaff
Sham Kakade
Wen Sun
OffRL
335
123
0
16 Jul 2020
Provably More Efficient Q-Learning in the One-Sided-Feedback/Full-Feedback Settings
Xiao-Yue Gong
D. Simchi-Levi
138
0
0
30 Jun 2020
Reinforcement Learning with Feedback Graphs
Christoph Dann
Yishay Mansour
M. Mohri
Ayush Sekhari
Karthik Sridharan
200
8
0
07 May 2020
1
Page 1 of 1
