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Comments on the Du-Kakade-Wang-Yang Lower Bounds

Comments on the Du-Kakade-Wang-Yang Lower Bounds

18 November 2019
Benjamin Van Roy
Shi Dong
ArXivPDFHTML

Papers citing "Comments on the Du-Kakade-Wang-Yang Lower Bounds"

17 / 17 papers shown
Title
Provable and Practical: Efficient Exploration in Reinforcement Learning
  via Langevin Monte Carlo
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo
Haque Ishfaq
Qingfeng Lan
Pan Xu
A. R. Mahmood
Doina Precup
Anima Anandkumar
Kamyar Azizzadenesheli
BDL
OffRL
30
20
0
29 May 2023
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
29
3
0
08 Mar 2022
Misspecified Gaussian Process Bandit Optimization
Misspecified Gaussian Process Bandit Optimization
Ilija Bogunovic
Andreas Krause
57
43
0
09 Nov 2021
Bad-Policy Density: A Measure of Reinforcement Learning Hardness
Bad-Policy Density: A Measure of Reinforcement Learning Hardness
David Abel
Cameron Allen
Dilip Arumugam
D Ellis Hershkowitz
Michael L. Littman
Lawson L. S. Wong
26
2
0
07 Oct 2021
Efficient Local Planning with Linear Function Approximation
Efficient Local Planning with Linear Function Approximation
Dong Yin
Botao Hao
Yasin Abbasi-Yadkori
N. Lazić
Csaba Szepesvári
34
19
0
12 Aug 2021
Bayesian decision-making under misspecified priors with applications to
  meta-learning
Bayesian decision-making under misspecified priors with applications to meta-learning
Max Simchowitz
Christopher Tosh
A. Krishnamurthy
Daniel J. Hsu
Thodoris Lykouris
Miroslav Dudík
Robert Schapire
40
49
0
03 Jul 2021
Which Mutual-Information Representation Learning Objectives are
  Sufficient for Control?
Which Mutual-Information Representation Learning Objectives are Sufficient for Control?
Kate Rakelly
Abhishek Gupta
Carlos Florensa
Sergey Levine
SSL
26
39
0
14 Jun 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
41
43
0
23 Mar 2021
On Function Approximation in Reinforcement Learning: Optimism in the
  Face of Large State Spaces
On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Spaces
Zhuoran Yang
Chi Jin
Zhaoran Wang
Mengdi Wang
Michael I. Jordan
44
18
0
09 Nov 2020
Efficient Planning in Large MDPs with Weak Linear Function Approximation
Efficient Planning in Large MDPs with Weak Linear Function Approximation
R. Shariff
Csaba Szepesvári
39
22
0
13 Jul 2020
Provably Efficient Reinforcement Learning for Discounted MDPs with
  Feature Mapping
Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping
Dongruo Zhou
Jiafan He
Quanquan Gu
35
133
0
23 Jun 2020
FLAMBE: Structural Complexity and Representation Learning of Low Rank
  MDPs
FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs
Alekh Agarwal
Sham Kakade
A. Krishnamurthy
Wen Sun
OffRL
41
223
0
18 Jun 2020
Bypassing the Monster: A Faster and Simpler Optimal Algorithm for
  Contextual Bandits under Realizability
Bypassing the Monster: A Faster and Simpler Optimal Algorithm for Contextual Bandits under Realizability
D. Simchi-Levi
Yunzong Xu
OffRL
47
107
0
28 Mar 2020
Provably Efficient Safe Exploration via Primal-Dual Policy Optimization
Provably Efficient Safe Exploration via Primal-Dual Policy Optimization
Dongsheng Ding
Xiaohan Wei
Zhuoran Yang
Zhaoran Wang
M. Jovanović
29
159
0
01 Mar 2020
Learning Near Optimal Policies with Low Inherent Bellman Error
Learning Near Optimal Policies with Low Inherent Bellman Error
Andrea Zanette
A. Lazaric
Mykel Kochenderfer
Emma Brunskill
OffRL
24
221
0
29 Feb 2020
Learning with Good Feature Representations in Bandits and in RL with a
  Generative Model
Learning with Good Feature Representations in Bandits and in RL with a Generative Model
Tor Lattimore
Csaba Szepesvári
Gellert Weisz
OffRL
31
168
0
18 Nov 2019
Is a Good Representation Sufficient for Sample Efficient Reinforcement
  Learning?
Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?
S. Du
Sham Kakade
Ruosong Wang
Lin F. Yang
47
192
0
07 Oct 2019
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