Graph Trend Filtering Networks for Recommendation-Reference-Cited by-同舟云学术

Graph Trend Filtering Networks for Recommendation

Published:2022-07-06 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Fan Wenqi¹,Liu Xiaorui²,Jin Wei²,Zhao Xiangyu³,Tang Jiliang²,Li Qing⁴

Affiliation:

1. The Hong Kong Polytechnic University, Hong Kong, UNK, Hong Kong

2. Michigan State University, East Lansing, MI, USA

3. City University of Hong Kong, Hong Kong, UNK, Hong Kong

4. The Hong Kong Polytechnic University, Hong Kong, UNK, China

Funder

City University of Hong Kong

SNAP

National Natural Science Foundation of China

CCF-Tencent Open Fund

the Army Research Office (ARO)

an internal research fund from The Hong Kong Polytechnic University

Home Depot

Cisco Systems Inc

General Research Fund from the Hong Kong Research Grants Council

National Science Foundation (NSF)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3477495.3531985

Reference57 articles.

1. Heinz H. Bauschke and Patrick L . Combettes . 2011 . Convex Analysis and Monotone Operator Theory in Hilbert Spaces 1st ed.). Springer Publishing Company , Incorporated. Heinz H. Bauschke and Patrick L. Combettes. 2011. Convex Analysis and Monotone Operator Theory in Hilbert Spaces 1st ed.). Springer Publishing Company, Incorporated.

2. Rianne van den Berg , Thomas N Kipf , and Max Welling . 2017. Graph convolutional matrix completion. arXiv preprint arXiv:1706.02263 ( 2017 ). Rianne van den Berg, Thomas N Kipf, and Max Welling. 2017. Graph convolutional matrix completion. arXiv preprint arXiv:1706.02263 (2017).

3. Bo Chen , Xiangyu Zhao , Yejing Wang , Wenqi Fan , Huifeng Guo , and Ruiming Tang . 2022 a. Automated Machine Learning for Deep Recommender Systems: A Survey. arXiv preprint arXiv:2204.01390 ( 2022 ). Bo Chen, Xiangyu Zhao, Yejing Wang, Wenqi Fan, Huifeng Guo, and Ruiming Tang. 2022 a. Automated Machine Learning for Deep Recommender Systems: A Survey. arXiv preprint arXiv:2204.01390 (2022).

4. Jingyuan Chen Hanwang Zhang Xiangnan He Liqiang Nie Wei Liu and Tat-Seng Chua. 2017. Attentive collaborative filtering: Multimedia recommendation with item-and component-level attention. In SIGIR. 335--344. Jingyuan Chen Hanwang Zhang Xiangnan He Liqiang Nie Wei Liu and Tat-Seng Chua. 2017. Attentive collaborative filtering: Multimedia recommendation with item-and component-level attention. In SIGIR. 335--344.

5. Jingfan Chen Guanghui Zhu Haojun Hou Chunfeng Yuan and Yihua Huang. 2022 b. AutoGSR: Neural Architecture Search for Graph-based Session Recommendation. In SIGIR . Jingfan Chen Guanghui Zhu Haojun Hou Chunfeng Yuan and Yihua Huang. 2022 b. AutoGSR: Neural Architecture Search for Graph-based Session Recommendation. In SIGIR .

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