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. 2302.10796
  4. Cited By
Provably Efficient Exploration in Quantum Reinforcement Learning with
  Logarithmic Worst-Case Regret

Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret

21 February 2023
Han Zhong
Jiachen Hu
Yecheng Xue
Tongyang Li
Liwei Wang
ArXivPDFHTML

Papers citing "Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret"

2 / 2 papers shown
Title
A General Framework for Sample-Efficient Function Approximation in
  Reinforcement Learning
A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
Zixiang Chen
C. J. Li
An Yuan
Quanquan Gu
Michael I. Jordan
OffRL
108
26
0
30 Sep 2022
Quantum Speedups of Optimizing Approximately Convex Functions with
  Applications to Logarithmic Regret Stochastic Convex Bandits
Quantum Speedups of Optimizing Approximately Convex Functions with Applications to Logarithmic Regret Stochastic Convex Bandits
Tongyang Li
Ruizhe Zhang
21
14
0
26 Sep 2022
1