Residual Multi-Task Learner for Applied Ranking-Reference-Cited by-同舟云学术

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Residual Multi-Task Learner for Applied Ranking

Published:2024-08-24 Issue: Volume:41 Page:4974-4985
ISSN:
Container-title:Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Fu Cong¹^ORCID,Wang Kun²^ORCID,Wu Jiahua¹^ORCID,Chen Yizhou¹^ORCID,Huzhang Guangda¹^ORCID,Ni Yabo³^ORCID,Zeng Anxiang⁴^ORCID,Zhou Zhiming⁵^ORCID

Affiliation:

1. Shopee Pte. Ltd., Singapore, Singapore

2. Shopee Pte. Ltd., Shanghai, China

3. Nanyang Technological University, Singapore, Singapore

4. SCSE, Nanyang Technological University, Singapore, Singapore

5. ECONCS, Shanghai University of Finance and Economics, Shanghai, China

Funder

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637528.3671523

Reference40 articles.

1. Gustavo EAPA Batista, Ronaldo C Prati, and Maria Carolina Monard. 2004. A study of the behavior of several methods for balancing machine learning training data. ACM SIGKDD explorations newsletter, Vol. 6, 1 (2004), 20--29.

2. A comparative analysis of offline and online evaluations and discussion of research paper recommender system evaluation

3. Rich Caruana. 1997. Multitask learning. Machine learning, Vol. 28 (1997), 41--75.

4. Nitesh V Chawla, Nathalie Japkowicz, and Aleksander Kotcz. 2004. Special issue on learning from imbalanced data sets. ACM SIGKDD explorations newsletter, Vol. 6, 1 (2004), 1--6.

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

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