Lightweight Embeddings for Graph Collaborative Filtering
Author:
Affiliation:
1. The University of Queensland, Brisbane, QLD, Australia
2. Shandong University, Jinan, China
3. Hefei University of Technology, Hefei, China
Funder
Australian Research Council Future Fellowship
Australian Research Council Discovery Early Career Researcher Award
Australian Research Council Discovery Project
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3626772.3657820
Reference69 articles.
1. Adi Ben-Israel and Thomas NE Greville. 2003. Generalized inverses: theory and applications. Vol. 15. Springer Science & Business Media.
2. Lei Chen Le Wu Richang Hong Kun Zhang and Meng Wang. 2020. Revisiting graph based collaborative filtering: A linear residual graph convolutional network approach. In AAAI.
3. Tong Chen Hongzhi Yin Yujia Zheng Zi Huang Yang Wang and Meng Wang. 2021. Learning elastic embeddings for customizing on-device recommenders. In SIGKDD.
4. Yizhou Chen Guangda Huzhang Anxiang Zeng Qingtao Yu Hui Sun Heng-Yi Li Jingyi Li Yabo Ni Han Yu and Zhiming Zhou. 2023. Clustered Embedding Learning for Recommender Systems. In WWW.
5. Weiyu Cheng, Yanyan Shen, and Linpeng Huang. 2020. Differentiable neural input search for recommender systems. arXiv preprint arXiv:2006.04466 (2020).
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