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On the Effectiveness of Sampled Softmax Loss for Item Recommendation

Jan 07, 2022
Jiancan Wu, Xiang Wang, Xingyu Gao, Jiawei Chen, Hongcheng Fu, Tianyu Qiu, Xiangnan He

* 10 Pages, 1 figure, 5 tables 

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Deconfounded Training for Graph Neural Networks

Dec 30, 2021
Yongduo Sui, Xiang Wang, Jiancan Wu, Xiangnan He, Tat-Seng Chua

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Learning Robust Recommender from Noisy Implicit Feedback

Dec 02, 2021
Wenjie Wang, Fuli Feng, Xiangnan He, Liqiang Nie, Tat-Seng Chua

* arXiv admin note: text overlap with arXiv:2006.04153 

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Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions

Sep 27, 2021
Chen Gao, Yu Zheng, Nian Li, Yinfeng Li, Yingrong Qin, Jinghua Piao, Yuhan Quan, Jianxin Chang, Depeng Jin, Xiangnan He, Yong Li

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Popularity Bias Is Not Always Evil: Disentangling Benign and Harmful Bias for Recommendation

Sep 16, 2021
Zihao Zhao, Jiawei Chen, Sheng Zhou, Xiangnan He, Xuezhi Cao, Fuzheng Zhang, Wei Wu

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DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network

Aug 22, 2021
Junkang Wu, Wentao Shi, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Fuzheng Zhang, Wei Wu, Xiangnan He

* CIKM2021 

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Causal Incremental Graph Convolution for Recommender System Retraining

Aug 16, 2021
Sihao Ding, Fuli Feng, Xiangnan He, Yong Liao, Jun Shi, Yongdong Zhang

* submitted to TNNLS 

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Time-aware Path Reasoning on Knowledge Graph for Recommendation

Aug 05, 2021
Yuyue Zhao, Xiang Wang, Jiawei Chen, Wei Tang, Yashen Wang, Xiangnan He, Haiyong Xie

* 22 pages, ACM Transactions on Information Systems (TOIS) Under Review 

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Exploring Lottery Ticket Hypothesis in Media Recommender Systems

Aug 02, 2021
Yanfang Wang, Yongduo Sui, Xiang Wang, Zhenguang Liu, Xiangnan He

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User-specific Adaptive Fine-tuning for Cross-domain Recommendations

Jun 18, 2021
Lei Chen, Fajie Yuan, Jiaxi Yang, Xiangnan He, Chengming Li, Min Yang

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Empowering Language Understanding with Counterfactual Reasoning

Jun 06, 2021
Fuli Feng, Jizhi Zhang, Xiangnan He, Hanwang Zhang, Tat-Seng Chua

* Accepted by Findings of ACL'21 

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Deconfounded Recommendation for Alleviating Bias Amplification

May 22, 2021
Wenjie Wang, Fuli Feng, Xiangnan He, Xiang Wang, Tat-Seng Chua

* Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discoveryand Data Mining (KDD 2021) 

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Probabilistic and Variational Recommendation Denoising

May 20, 2021
Yu Wang, Xin Xin, Zaiqiao Meng, Xiangnan He, Joemon Jose, Fuli Feng

* 13 pages, 17 figures 

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Graph Learning based Recommender Systems: A Review

May 13, 2021
Shoujin Wang, Liang Hu, Yan Wang, Xiangnan He, Quan Z. Sheng, Mehmet A. Orgun, Longbing Cao, Francesco Ricci, Philip S. Yu

* Accepted by IJCAI 2021 Survey Track, copyright is owned to IJCAI. The first systematic survey on graph learning based recommender systems. arXiv admin note: text overlap with arXiv:2004.11718 

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Causal Intervention for Leveraging Popularity Bias in Recommendation

May 13, 2021
Yang Zhang, Fuli Feng, Xiangnan He, Tianxin Wei, Chonggang Song, Guohui Ling, Yongdong Zhang

* Appear in SIGIR 2021 

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AutoDebias: Learning to Debias for Recommendation

May 10, 2021
Jiawei Chen, Hande Dong, Yang Qiu, Xiangnan He, Xin Xin, Liang Chen, Guli Lin, Keping Yang

* Accepted by SIGIR 2021 

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A Survey on Neural Recommendation: From Collaborative Filtering to Content and Context Enriched Recommendation

Apr 27, 2021
Le Wu, Xiangnan He, Xiang Wang, Kun Zhang, Meng Wang

* In submission 

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Structure-Enhanced Meta-Learning For Few-Shot Graph Classification

Mar 11, 2021
Shunyu Jiang, Fuli Feng, Weijian Chen, Xiang Li, Xiangnan He

* Submitted to AI Open 

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Learning Intents behind Interactions with Knowledge Graph for Recommendation

Feb 14, 2021
Xiang Wang, Tinglin Huang, Dingxian Wang, Yancheng Yuan, Zhenguang Liu, Xiangnan He, Tat-Seng Chua

* WWW 2021 oral presentation 

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Advances and Challenges in Conversational Recommender Systems: A Survey

Feb 07, 2021
Chongming Gao, Wenqiang Lei, Xiangnan He, Maarten de Rijke, Tat-Seng Chua

* 30 pages, 8 figures 

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On the Equivalence of Decoupled Graph Convolution Network and Label Propagation

Oct 23, 2020
Hande Dong, Jiawei Chen, Fuli Feng, Xiangnan He, Shuxian Bi, Zhaolin Ding, Peng Cui

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Should Graph Convolution Trust Neighbors? A Simple Causal Inference Method

Oct 22, 2020
Fuli Feng, Weiran Huang, Xin Xin, Xiangnan He, Tat-Seng Chua

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Self-supervised Graph Learning for Recommendation

Oct 21, 2020
Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian, Xing Xie

* 11 pages, 7 pages, 5 tables 

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CatGCN: Graph Convolutional Networks with Categorical Node Features

Sep 17, 2020
Weijian Chen, Fuli Feng, Qifan Wang, Xiangnan He, Chonggang Song, Guohui Ling, Yongdong Zhang

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