Invariant Collaborative Filtering to Popularity Distribution Shift-Reference-Cited by-同舟云学术

Invariant Collaborative Filtering to Popularity Distribution Shift

Published:2023-04-30 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the ACM Web Conference 2023
language:
Short-container-title:

Author:

Zhang An¹^ORCID,Zheng Jingnan²^ORCID,Wang Xiang³^ORCID,Yuan Yancheng⁴^ORCID,Chua Tat-Seng¹^ORCID

Affiliation:

1. Sea-NExT Joint Lab, National University of Singapore, Singapore

2. National University of Singapore, Singapore

3. University of Science and Technology of China, China and Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, China

4. The Hong Kong Polytechnic University, Hong Kong

Funder

CCCD Key Lab of Ministry of Culture and Tourism

Sea-NExT Joint Lab

National Natural Science Foundation of China

University Synergy Innovation Program of Anhui Province

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3543507.3583461

Reference59 articles.

1. Himan Abdollahpouri Robin Burke and Bamshad Mobasher. 2017. Controlling Popularity Bias in Learning-to-Rank Recommendation. In RecSys. Himan Abdollahpouri Robin Burke and Bamshad Mobasher. 2017. Controlling Popularity Bias in Learning-to-Rank Recommendation. In RecSys.

2. Himan Abdollahpouri , Robin Burke , and Bamshad Mobasher . 2019 . Managing Popularity Bias in Recommender Systems with Personalized Re-Ranking. In FLAIRS Conference. Himan Abdollahpouri, Robin Burke, and Bamshad Mobasher. 2019. Managing Popularity Bias in Recommender Systems with Personalized Re-Ranking. In FLAIRS Conference.

3. Martin Arjovsky Léon Bottou Ishaan Gulrajani and David Lopez-Paz. 2019. Invariant risk minimization. arXiv preprint arXiv:1907.02893. Martin Arjovsky Léon Bottou Ishaan Gulrajani and David Lopez-Paz. 2019. Invariant risk minimization. arXiv preprint arXiv:1907.02893.

4. Yoshua Bengio and Jean-Sébastien Senecal. 2003. Quick Training of Probabilistic Neural Nets by Importance Sampling. In AISTATS. Yoshua Bengio and Jean-Sébastien Senecal. 2003. Quick Training of Probabilistic Neural Nets by Importance Sampling. In AISTATS.

5. Stephen Bonner and Flavian Vasile. 2018. Causal embeddings for recommendation. In RecSys. Stephen Bonner and Flavian Vasile. 2018. Causal embeddings for recommendation. In RecSys.

Cited by 19 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. ORCDF: An Oversmoothing-Resistant Cognitive Diagnosis Framework for Student Learning in Online Education Systems;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

2. Popularity-Aware Alignment and Contrast for Mitigating Popularity Bias;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

3. Modeling item exposure and user satisfaction for debiased recommendation with causal inference;Information Sciences;2024-08

4. NFARec: A Negative Feedback-Aware Recommender Model;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10

5. On Generative Agents in Recommendation;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10