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. 2202.10887
  4. Cited By
Policy Evaluation for Temporal and/or Spatial Dependent Experiments

Policy Evaluation for Temporal and/or Spatial Dependent Experiments

22 February 2022
S. Luo
Ying Yang
Chengchun Shi
Fang Yao
Jieping Ye
Hongtu Zhu
ArXivPDFHTML

Papers citing "Policy Evaluation for Temporal and/or Spatial Dependent Experiments"

4 / 4 papers shown
Title
A Multi-Agent Reinforcement Learning Framework for Off-Policy Evaluation
  in Two-sided Markets
A Multi-Agent Reinforcement Learning Framework for Off-Policy Evaluation in Two-sided Markets
C. Shi
Runzhe Wan
Ge Song
S. Luo
R. Song
Hongtu Zhu
OffRL
20
6
0
21 Feb 2022
Reinforcement Learning for Ridesharing: An Extended Survey
Reinforcement Learning for Ridesharing: An Extended Survey
Zhiwei Qin
Hongtu Zhu
Jieping Ye
19
57
0
03 May 2021
Optimal Approximation Rate of ReLU Networks in terms of Width and Depth
Optimal Approximation Rate of ReLU Networks in terms of Width and Depth
Zuowei Shen
Haizhao Yang
Shijun Zhang
69
85
0
28 Feb 2021
Double Reinforcement Learning for Efficient Off-Policy Evaluation in
  Markov Decision Processes
Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes
Nathan Kallus
Masatoshi Uehara
OffRL
17
159
0
22 Aug 2019
1