Doubly Calibrated Estimator for Recommendation on Data Missing Not at Random-Reference-Cited by-同舟云学术

Doubly Calibrated Estimator for Recommendation on Data Missing Not at Random

Published:2024-05-13 Issue: Volume:41 Page:3810-3820
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Container-title:Proceedings of the ACM Web Conference 2024
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Author:

Kweon Wonbin¹^ORCID,Yu Hwanjo¹^ORCID

Affiliation:

1. Pohang University of Science and Technology, Pohang, Republic of Korea

Funder

NRF

NRF, MSIT

MSIT

Ministry of Education

IITP

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3589334.3645617

Reference54 articles.

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3. Tianfeng Chai and Roland R Draxler. 2014. Root mean square error (RMSE) or mean absolute error (MAE)?--Arguments against avoiding RMSE in the literature. Geoscientific model development 7, 3 (2014), 1247--1250.

4. Jiawei Chen Hande Dong Yang Qiu Xiangnan He Xin Xin Liang Chen Guli Lin and Keping Yang. 2021. AutoDebias: Learning to debias for recommendation. In SIGIR.

5. Bias and debias in recommender system: A survey and future directions;Chen Jiawei;ACM Transactions on Information Systems,2023

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