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Graph neural network (GNN) is a powerful learning approach for graph-based recommender systems.
Learning matrix space image representations
Anand Rangarajan · 2001
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Matrix factorization techniques for recommender systems
Yehuda Koren, Robert Bell, and Chris Volinsky · 2009
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Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
Nathan Halko, Per-Gunnar Martinsson, and Joel A Tropp · 2011
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Image denoising using the higher order singular value decomposition
Ajit Rajwade, Anand Rangarajan, and Arunava Banerjee · 2012
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Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, and Tat-Seng Chua · 2017
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Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Deep graph infomax
Petar Velickovic, William Fedus, William L Hamilton, Pietro Liò, Yoshua Bengio, and R Devon Hjelm · 2019
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Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng, and Tat-Seng Chua · 2019
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Xiangnan He, Kuan Deng, Xiang Wang, Yan Li, Yongdong Zhang, and Meng Wang · 2020
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Zhen Peng, Wenbing Huang, Minnan Luo, Qinghua Zheng, Yu Rong, Tingyang Xu, and Junzhou Huang · 2020
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Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, and Yang Shen · 2020
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Automated self-supervised learning for graphs
Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, and Jiliang Tang · 2022
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Improving graph collaborative filtering with neighborhood-enriched contrastive learning
Zihan Lin, Changxin Tian, Yupeng Hou, and Wayne Xin Zhao · 2022
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Robust tensor graph convolutional networks via t-svd based graph augmentation
Zhebin Wu, Lin Shu, Ziyue Xu, Yaomin Chang, Chuan Chen, and Zibin Zheng · 2022
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Self-supervised hypergraph transformer for recommender systems
Lianghao Xia, Chao Huang, and Chuxu Zhang · 2022
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Contrastive learning for sequential recommendation
Xu Xie, Fei Sun, Zhaoyang Liu, Shiwen Wu, Jinyang Gao, Jiandong Zhang, Bolin Ding, and Bin Cui · 2022
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Adversarial graph augmentation to improve graph contrastive learning
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Measuring and relieving the over-smoothing problem for graph neural networks from the topological view
Deli Chen, Yankai Lin, Wei Li, Peng Li, Jie Zhou, and Xu Sun
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Revisiting graph based collaborative filtering: A linear residual graph convolutional network approach
Lei Chen, Le Wu, Richang Hong, Kun Zhang, and Meng Wang
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Autogcl: Automated graph contrastive learning via learnable view generators
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Enhancing sequential recommendation with graph contrastive learning
Yixin Zhang, Yong Liu, Yonghui Xu, Hao Xiong, Chenyi Lei, Wei He, Lizhen Cui, and Chunyan Miao · 2022
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Graph contrastive learning with adaptive augmentation
Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, and Liang Wang · 2080
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