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Counterfactually Evaluating Explanations in Recommender Systems
v1v2 (latest)

Counterfactually Evaluating Explanations in Recommender Systems

2 March 2022
Yuanshun Yao
Chong Wang
Hang Li
    OffRLLRM
ArXiv (abs)PDFHTML

Papers citing "Counterfactually Evaluating Explanations in Recommender Systems"

3 / 3 papers shown
Exploring the Landscape of Machine Unlearning: A Comprehensive Survey
  and Taxonomy
Exploring the Landscape of Machine Unlearning: A Comprehensive Survey and TaxonomyIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023
T. Shaik
Xiaohui Tao
Haoran Xie
Lin Li
Xiaofeng Zhu
Qingyuan Li
MU
529
58
0
10 May 2023
Counterfactual Explanations and Algorithmic Recourses for Machine
  Learning: A Review
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A ReviewACM Computing Surveys (ACM CSUR), 2020
Sahil Verma
Varich Boonsanong
Minh Hoang
Keegan E. Hines
John P. Dickerson
Chirag Shah
CML
730
257
0
20 Oct 2020
PRINCE: Provider-side Interpretability with Counterfactual Explanations
  in Recommender Systems
PRINCE: Provider-side Interpretability with Counterfactual Explanations in Recommender SystemsWeb Search and Data Mining (WSDM), 2019
Azin Ghazimatin
Oana Balalau
Rishiraj Saha Roy
Gerhard Weikum
FAtt
418
104
0
19 Nov 2019
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