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. 2203.17118
  4. Cited By
Doubly-Robust Estimation for Correcting Position-Bias in Click Feedback
  for Unbiased Learning to Rank

Doubly-Robust Estimation for Correcting Position-Bias in Click Feedback for Unbiased Learning to Rank

31 March 2022
Harrie Oosterhuis
    CML
ArXivPDFHTML

Papers citing "Doubly-Robust Estimation for Correcting Position-Bias in Click Feedback for Unbiased Learning to Rank"

11 / 11 papers shown
Title
Ranking Policy Learning via Marketplace Expected Value Estimation From
  Observational Data
Ranking Policy Learning via Marketplace Expected Value Estimation From Observational Data
Ehsan Ebrahimzadeh
Nikhil Monga
Hang Gao
Alex Cozzi
Abraham Bagherjeiran
CML
OffRL
27
0
0
06 Oct 2024
Proximal Ranking Policy Optimization for Practical Safety in
  Counterfactual Learning to Rank
Proximal Ranking Policy Optimization for Practical Safety in Counterfactual Learning to Rank
Shashank Gupta
Harrie Oosterhuis
Maarten de Rijke
OffRL
32
0
0
15 Sep 2024
Practical and Robust Safety Guarantees for Advanced Counterfactual
  Learning to Rank
Practical and Robust Safety Guarantees for Advanced Counterfactual Learning to Rank
Shashank Gupta
Harrie Oosterhuis
Maarten de Rijke
37
6
0
29 Jul 2024
Debiased Recommendation with Noisy Feedback
Debiased Recommendation with Noisy Feedback
Haoxuan Li
Chunyuan Zheng
Wenjie Wang
Hao Wang
Fuli Feng
Xiao-Hua Zhou
43
7
0
24 Jun 2024
Investigating the Robustness of Counterfactual Learning to Rank Models:
  A Reproducibility Study
Investigating the Robustness of Counterfactual Learning to Rank Models: A Reproducibility Study
Zechun Niu
Jiaxin Mao
Qingyao Ai
Ji-Rong Wen
112
0
0
04 Apr 2024
Identifiability Matters: Revealing the Hidden Recoverable Condition in
  Unbiased Learning to Rank
Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank
Mouxiang Chen
Chenghao Liu
Zemin Liu
Zhuo Li
Jianling Sun
CML
26
2
0
27 Sep 2023
Double Clipping: Less-Biased Variance Reduction in Off-Policy Evaluation
Double Clipping: Less-Biased Variance Reduction in Off-Policy Evaluation
Jan Malte Lichtenberg
Alexander K. Buchholz
Giuseppe Di Benedetto
M. Ruffini
Ben London
OffRL
23
2
0
03 Sep 2023
On (Normalised) Discounted Cumulative Gain as an Off-Policy Evaluation
  Metric for Top-$n$ Recommendation
On (Normalised) Discounted Cumulative Gain as an Off-Policy Evaluation Metric for Top-nnn Recommendation
Olivier Jeunen
Ivan Potapov
Aleksei Ustimenko
ELM
OffRL
27
11
0
27 Jul 2023
Unified Off-Policy Learning to Rank: a Reinforcement Learning
  Perspective
Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective
Zeyu Zhang
Yi-Hsun Su
Hui Yuan
Yiran Wu
R. Balasubramanian
Qingyun Wu
Huazheng Wang
Mengdi Wang
OffRL
CML
36
4
0
13 Jun 2023
Recent Advances in the Foundations and Applications of Unbiased Learning
  to Rank
Recent Advances in the Foundations and Applications of Unbiased Learning to Rank
Shashank Gupta
Philipp Hager
Jin Huang
Ali Vardasbi
Harrie Oosterhuis
OffRL
35
5
0
04 May 2023
StochasticRank: Global Optimization of Scale-Free Discrete Functions
StochasticRank: Global Optimization of Scale-Free Discrete Functions
Aleksei Ustimenko
Liudmila Prokhorenkova
40
19
0
04 Mar 2020
1