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Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation

Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation

21 February 2020
Yaqi Duan
Mengdi Wang
    OffRL
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Papers citing "Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation"

43 / 43 papers shown
Title
Leveraging Unlabeled Data Sharing through Kernel Function Approximation in Offline Reinforcement Learning
Leveraging Unlabeled Data Sharing through Kernel Function Approximation in Offline Reinforcement Learning
Yen-Ru Lai
Fu-Chieh Chang
Pei-Yuan Wu
OffRL
81
1
0
22 Aug 2024
From Words to Actions: Unveiling the Theoretical Underpinnings of
  LLM-Driven Autonomous Systems
From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems
Jianliang He
Siyu Chen
Fengzhuo Zhang
Zhuoran Yang
LM&Ro
LLMAG
44
2
0
30 May 2024
Imitation Learning in Discounted Linear MDPs without exploration
  assumptions
Imitation Learning in Discounted Linear MDPs without exploration assumptions
Luca Viano
Stratis Skoulakis
V. Cevher
30
3
0
03 May 2024
Multiple-policy Evaluation via Density Estimation
Multiple-policy Evaluation via Density Estimation
Yilei Chen
Aldo Pacchiano
I. Paschalidis
OffRL
32
0
0
29 Mar 2024
On the Curses of Future and History in Future-dependent Value Functions
  for Off-policy Evaluation
On the Curses of Future and History in Future-dependent Value Functions for Off-policy Evaluation
Yuheng Zhang
Nan Jiang
OffRL
29
4
0
22 Feb 2024
On Sample-Efficient Offline Reinforcement Learning: Data Diversity,
  Posterior Sampling, and Beyond
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling, and Beyond
Thanh Nguyen-Tang
Raman Arora
OffRL
33
3
0
06 Jan 2024
Conservative Exploration for Policy Optimization via Off-Policy Policy
  Evaluation
Conservative Exploration for Policy Optimization via Off-Policy Policy Evaluation
Paul Daoudi
Mathias Formoso
Othman Gaizi
Achraf Azize
Evrard Garcelon
OffRL
26
0
0
24 Dec 2023
Stackelberg Batch Policy Learning
Stackelberg Batch Policy Learning
Wenzhuo Zhou
Annie Qu
OffRL
35
1
0
28 Sep 2023
The Optimal Approximation Factors in Misspecified Off-Policy Value
  Function Estimation
The Optimal Approximation Factors in Misspecified Off-Policy Value Function Estimation
P. Amortila
Nan Jiang
Csaba Szepesvári
OffRL
29
3
0
25 Jul 2023
High-probability sample complexities for policy evaluation with linear
  function approximation
High-probability sample complexities for policy evaluation with linear function approximation
Gen Li
Weichen Wu
Yuejie Chi
Cong Ma
Alessandro Rinaldo
Yuting Wei
OffRL
30
7
0
30 May 2023
Reinforcement Learning with Human Feedback: Learning Dynamic Choices via
  Pessimism
Reinforcement Learning with Human Feedback: Learning Dynamic Choices via Pessimism
Zihao Li
Zhuoran Yang
Mengdi Wang
OffRL
37
55
0
29 May 2023
A Review of Off-Policy Evaluation in Reinforcement Learning
A Review of Off-Policy Evaluation in Reinforcement Learning
Masatoshi Uehara
C. Shi
Nathan Kallus
OffRL
36
69
0
13 Dec 2022
Counterfactual Learning with General Data-generating Policies
Counterfactual Learning with General Data-generating Policies
Yusuke Narita
Kyohei Okumura
Akihiro Shimizu
Kohei Yata
CML
OffRL
19
0
0
04 Dec 2022
Offline Policy Evaluation and Optimization under Confounding
Offline Policy Evaluation and Optimization under Confounding
Chinmaya Kausik
Yangyi Lu
Kevin Tan
Maggie Makar
Yixin Wang
Ambuj Tewari
OffRL
26
8
0
29 Nov 2022
On Instance-Dependent Bounds for Offline Reinforcement Learning with
  Linear Function Approximation
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation
Thanh Nguyen-Tang
Ming Yin
Sunil R. Gupta
Svetha Venkatesh
R. Arora
OffRL
58
16
0
23 Nov 2022
When is Realizability Sufficient for Off-Policy Reinforcement Learning?
When is Realizability Sufficient for Off-Policy Reinforcement Learning?
Andrea Zanette
OffRL
24
14
0
10 Nov 2022
Beyond the Return: Off-policy Function Estimation under User-specified
  Error-measuring Distributions
Beyond the Return: Off-policy Function Estimation under User-specified Error-measuring Distributions
Audrey Huang
Nan Jiang
OffRL
55
9
0
27 Oct 2022
Statistical Estimation of Confounded Linear MDPs: An Instrumental
  Variable Approach
Statistical Estimation of Confounded Linear MDPs: An Instrumental Variable Approach
Miao Lu
Wenhao Yang
Liangyu Zhang
Zhihua Zhang
OffRL
40
1
0
12 Sep 2022
Strategic Decision-Making in the Presence of Information Asymmetry:
  Provably Efficient RL with Algorithmic Instruments
Strategic Decision-Making in the Presence of Information Asymmetry: Provably Efficient RL with Algorithmic Instruments
Mengxin Yu
Zhuoran Yang
Jianqing Fan
OffRL
21
8
0
23 Aug 2022
Provably Efficient Reinforcement Learning in Partially Observable
  Dynamical Systems
Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems
Masatoshi Uehara
Ayush Sekhari
Jason D. Lee
Nathan Kallus
Wen Sun
OffRL
51
32
0
24 Jun 2022
Federated Offline Reinforcement Learning
Federated Offline Reinforcement Learning
D. Zhou
Yufeng Zhang
Aaron Sonabend-W
Zhaoran Wang
Junwei Lu
Tianxi Cai
OffRL
40
13
0
11 Jun 2022
Offline Stochastic Shortest Path: Learning, Evaluation and Towards
  Optimality
Offline Stochastic Shortest Path: Learning, Evaluation and Towards Optimality
Ming Yin
Wenjing Chen
Mengdi Wang
Yu-Xiang Wang
OffRL
30
4
0
10 Jun 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
34
66
0
11 Mar 2022
A Complete Characterization of Linear Estimators for Offline Policy
  Evaluation
A Complete Characterization of Linear Estimators for Offline Policy Evaluation
Juan C. Perdomo
A. Krishnamurthy
Peter L. Bartlett
Sham Kakade
OffRL
27
3
0
08 Mar 2022
Off-Policy Fitted Q-Evaluation with Differentiable Function
  Approximators: Z-Estimation and Inference Theory
Off-Policy Fitted Q-Evaluation with Differentiable Function Approximators: Z-Estimation and Inference Theory
Ruiqi Zhang
Xuezhou Zhang
Chengzhuo Ni
Mengdi Wang
OffRL
35
16
0
10 Feb 2022
Hyperparameter Selection Methods for Fitted Q-Evaluation with Error
  Guarantee
Hyperparameter Selection Methods for Fitted Q-Evaluation with Error Guarantee
Kohei Miyaguchi
OffRL
43
1
0
07 Jan 2022
DR3: Value-Based Deep Reinforcement Learning Requires Explicit
  Regularization
DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization
Aviral Kumar
Rishabh Agarwal
Tengyu Ma
Aaron Courville
George Tucker
Sergey Levine
OffRL
31
65
0
09 Dec 2021
Offline Neural Contextual Bandits: Pessimism, Optimization and
  Generalization
Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization
Thanh Nguyen-Tang
Sunil R. Gupta
A. Nguyen
Svetha Venkatesh
OffRL
31
29
0
27 Nov 2021
The Impact of Data Distribution on Q-learning with Function
  Approximation
The Impact of Data Distribution on Q-learning with Function Approximation
Pedro P. Santos
Diogo S. Carvalho
A. Sardinha
Francisco S. Melo
OffRL
19
2
0
23 Nov 2021
Explaining Off-Policy Actor-Critic From A Bias-Variance Perspective
Explaining Off-Policy Actor-Critic From A Bias-Variance Perspective
Ting-Han Fan
Peter J. Ramadge
CML
FAtt
OffRL
21
2
0
06 Oct 2021
Provable Benefits of Actor-Critic Methods for Offline Reinforcement
  Learning
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning
Andrea Zanette
Martin J. Wainwright
Emma Brunskill
OffRL
29
115
0
19 Aug 2021
Variance-Aware Off-Policy Evaluation with Linear Function Approximation
Variance-Aware Off-Policy Evaluation with Linear Function Approximation
Yifei Min
Tianhao Wang
Dongruo Zhou
Quanquan Gu
OffRL
37
38
0
22 Jun 2021
Offline RL Without Off-Policy Evaluation
Offline RL Without Off-Policy Evaluation
David Brandfonbrener
William F. Whitney
Rajesh Ranganath
Joan Bruna
OffRL
42
162
0
16 Jun 2021
Bellman-consistent Pessimism for Offline Reinforcement Learning
Bellman-consistent Pessimism for Offline Reinforcement Learning
Tengyang Xie
Ching-An Cheng
Nan Jiang
Paul Mineiro
Alekh Agarwal
OffRL
LRM
27
270
0
13 Jun 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
Nearly Horizon-Free Offline Reinforcement Learning
Nearly Horizon-Free Offline Reinforcement Learning
Tongzheng Ren
Jialian Li
Bo Dai
S. Du
Sujay Sanghavi
OffRL
32
49
0
25 Mar 2021
Infinite-Horizon Offline Reinforcement Learning with Linear Function
  Approximation: Curse of Dimensionality and Algorithm
Infinite-Horizon Offline Reinforcement Learning with Linear Function Approximation: Curse of Dimensionality and Algorithm
Lin Chen
B. Scherrer
Peter L. Bartlett
OffRL
83
16
0
17 Mar 2021
Instabilities of Offline RL with Pre-Trained Neural Representation
Instabilities of Offline RL with Pre-Trained Neural Representation
Ruosong Wang
Yifan Wu
Ruslan Salakhutdinov
Sham Kakade
OffRL
20
42
0
08 Mar 2021
Fast Rates for the Regret of Offline Reinforcement Learning
Fast Rates for the Regret of Offline Reinforcement Learning
Yichun Hu
Nathan Kallus
Masatoshi Uehara
OffRL
15
30
0
31 Jan 2021
Is Pessimism Provably Efficient for Offline RL?
Is Pessimism Provably Efficient for Offline RL?
Ying Jin
Zhuoran Yang
Zhaoran Wang
OffRL
27
349
0
30 Dec 2020
Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can
  be Exponentially Harder than Online RL
Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL
Andrea Zanette
OffRL
26
71
0
14 Dec 2020
Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation
  for Reinforcement Learning
Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning
Ming Yin
Yu Bai
Yu-Xiang Wang
OffRL
41
31
0
07 Jul 2020
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning
  with a Generative Model
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model
Gen Li
Yuting Wei
Yuejie Chi
Yuxin Chen
34
125
0
26 May 2020
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