Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales

Terms and Conditions

Twitter GitHub LinkedIn Bluesky Youtube

© 2026 ResearchTrend.AI, All rights reserved.

Home
Papers
2102.02049
Cited By

On Query-efficient Planning in MDPs under Linear Realizability of the
Optimal State-value Function

v1v2v3 (latest)

On Query-efficient Planning in MDPs under Linear Realizability of the Optimal State-value Function

Annual Conference Computational Learning Theory (COLT), 2021

3 February 2021

Philip Amortila

Barnabás Janzer

Yasin Abbasi-Yadkori

Csaba Szepesvári

ArXiv (abs)PDF HTML

Papers citing "On Query-efficient Planning in MDPs under Linear Realizability of the Optimal State-value Function"

16 / 16 papers shown

Hybrid Reinforcement Learning from Offline Observation Alone

Hybrid Reinforcement Learning from Offline Observation Alone

J. Andrew Bagnell

349

6

0

11 Jun 2024

RL in Markov Games with Independent Function Approximation: Improved
Sample Complexity Bound under the Local Access Model

RL in Markov Games with Independent Function Approximation: Improved Sample Complexity Bound under the Local Access ModelInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024

501

1

0

18 Mar 2024

Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for
Dimension-Dependent Adaptivity

Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent AdaptivityInternational Conference on Learning Representations (ICLR), 2023

Emmeran Johnson

Ciara Pike-Burke

Patrick Rebeschini

382

2

0

02 Oct 2023

Hardness of Independent Learning and Sparse Equilibrium Computation in
Markov Games

Hardness of Independent Learning and Sparse Equilibrium Computation in Markov GamesInternational Conference on Machine Learning (ICML), 2023

Dylan J. Foster

287

14

0

22 Mar 2023

Exponential Hardness of Reinforcement Learning with Linear Function
Approximation

Exponential Hardness of Reinforcement Learning with Linear Function ApproximationAnnual Conference Computational Learning Theory (COLT), 2023

Csaba Szepesvári

301

6

0

25 Feb 2023

Linear Reinforcement Learning with Ball Structure Action Space

Linear Reinforcement Learning with Ball Structure Action SpaceInternational Conference on Algorithmic Learning Theory (ALT), 2022

Dean Phillips Foster

203

1

0

14 Nov 2022

A Few Expert Queries Suffices for Sample-Efficient RL with Resets and
Linear Value Approximation

A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value ApproximationNeural Information Processing Systems (NeurIPS), 2022

Philip Amortila

Dean Phillips Foster

254

6

0

18 Jul 2022

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

On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RLNeural Information Processing Systems (NeurIPS), 2022

A. Krishnamurthy

416

29

0

21 Jun 2022

Learning in Observable POMDPs, without Computationally Intractable
Oracles

Learning in Observable POMDPs, without Computationally Intractable OraclesNeural Information Processing Systems (NeurIPS), 2022

279

33

0

07 Jun 2022

Computational-Statistical Gaps in Reinforcement Learning

Computational-Statistical Gaps in Reinforcement Learning

192

5

0

11 Feb 2022

TensorPlan and the Few Actions Lower Bound for Planning in MDPs under
Linear Realizability of Optimal Value Functions

TensorPlan and the Few Actions Lower Bound for Planning in MDPs under Linear Realizability of Optimal Value Functions

Csaba Szepesvári

175

8

0

05 Oct 2021

A Boosting Approach to Reinforcement Learning

A Boosting Approach to Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2021

259

15

0

22 Aug 2021

Efficient Local Planning with Linear Function Approximation

Efficient Local Planning with Linear Function ApproximationInternational Conference on Algorithmic Learning Theory (ALT), 2021

Yasin Abbasi-Yadkori

Csaba Szepesvári

419

24

0

12 Aug 2021

Sample Efficient Reinforcement Learning In Continuous State Spaces: A
Perspective Beyond Linearity

Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond LinearityInternational Conference on Machine Learning (ICML), 2021

Vishwak Srinivasan

190

7

0

15 Jun 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 RevisitingNeural Information Processing Systems (NeurIPS), 2021

325

33

0

17 May 2021

When Is Generalizable Reinforcement Learning Tractable?

When Is Generalizable Reinforcement Learning Tractable?Neural Information Processing Systems (NeurIPS), 2021

Pradeep Ravikumar

623

27

0

01 Jan 2021

Page 1 of 1