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ORCIDXiangnan He 0001
Person information
- affiliation: University of Science and Technology of China, School of Information Science and Technology, Hefei, China
- affiliation (PhD 2016): National University of Singapore, School of Computing, Singapore
Other persons with the same name
- Xiangnan He 0002 — Fudan University, Shanghai, China
- Xiangnan He 0003 — Southern University of Science and Technology, Shenzhen, China
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2020 – today
- 2023
[j64]Yuan Gao, Xiang Wang, Xiangnan He, Huamin Feng, Yong-Dong Zhang:
Rumor detection with self-supervised learning on texts and social graph. Frontiers Comput. Sci. 17(4): 174611 (2023)- [j63]Xiang Wang
, Yingxin Wu, An Zhang, Fuli Feng, Xiangnan He, Tat-Seng Chua:
Reinforced Causal Explainer for Graph Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 2297-2309 (2023) - [j62]Kang Liu, Feng Xue, Xiangnan He, Dan Guo, Richang Hong:
Joint Multi-Grained Popularity-Aware Graph Convolution Collaborative Filtering for Recommendation. IEEE Trans. Comput. Soc. Syst. 10(1): 72-83 (2023) - [j61]Jintang Li, Tao Xie, Liang Chen, Fenfang Xie, Xiangnan He, Zibin Zheng:
Adversarial Attack on Large Scale Graph. IEEE Trans. Knowl. Data Eng. 35(1): 82-95 (2023) - [j60]Fuli Feng, Xiangnan He, Hanwang Zhang, Tat-Seng Chua:
Cross-GCN: Enhancing Graph Convolutional Network with $k$k-Order Feature Interactions. IEEE Trans. Knowl. Data Eng. 35(1): 225-236 (2023) - [j59]Yu Zheng, Chen Gao, Xiangnan He, Depeng Jin, Yong Li:
Incorporating Price into Recommendation With Graph Convolutional Networks. IEEE Trans. Knowl. Data Eng. 35(2): 1609-1623 (2023) - [j58]Jianxin Chang, Chen Gao, Xiangnan He, Depeng Jin, Yong Li:
Bundle Recommendation and Generation With Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 35(3): 2326-2340 (2023) - [j57]Lei Chen, Fajie Yuan, Jiaxi Yang, Xiangnan He, Chengming Li, Min Yang:
User-Specific Adaptive Fine-Tuning for Cross-Domain Recommendations. IEEE Trans. Knowl. Data Eng. 35(3): 3239-3252 (2023) - [j56]Weijian Chen, Fuli Feng, Qifan Wang, Xiangnan He, Chonggang Song, Guohui Ling, Yongdong Zhang:
CatGCN: Graph Convolutional Networks With Categorical Node Features. IEEE Trans. Knowl. Data Eng. 35(4): 3500-3511 (2023) - [j55]Le Wu, Xiangnan He, Xiang Wang, Kun Zhang, Meng Wang:
A Survey on Accuracy-Oriented Neural Recommendation: From Collaborative Filtering to Information-Rich Recommendation. IEEE Trans. Knowl. Data Eng. 35(5): 4425-4445 (2023) - [j54]Jiajia Chen, Xin Xin, Xianfeng Liang, Xiangnan He, Jun Liu:
GDSRec: Graph-Based Decentralized Collaborative Filtering for Social Recommendation. IEEE Trans. Knowl. Data Eng. 35(5): 4813-4824 (2023) - [j53]Yuyue Zhao, Xiang Wang, Jiawei Chen, Yashen Wang, Wei Tang, Xiangnan He, Haiyong Xie:
Time-aware Path Reasoning on Knowledge Graph for Recommendation. ACM Trans. Inf. Syst. 41(2): 26:1-26:26 (2023) - [j52]Shuo Wang, Huixia Ben, Yanbin Hao, Xiangnan He, Meng Wang:
Boosting Hyperspectral Image Classification with Dual Hierarchical Learning. ACM Trans. Multim. Comput. Commun. Appl. 19(1): 21:1-21:19 (2023) - [c157]Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang:
Alleviating Structural Distribution Shift in Graph Anomaly Detection. WSDM 2023: 357-365 - [c156]Junfeng Fang, Xiang Wang, An Zhang, Zemin Liu, Xiangnan He, Tat-Seng Chua:
Cooperative Explanations of Graph Neural Networks. WSDM 2023: 616-624 - [c155]Gang Chen, Jiawei Chen, Fuli Feng, Sheng Zhou, Xiangnan He:
Unbiased Knowledge Distillation for Recommendation. WSDM 2023: 976-984 - [c154]Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui, Xiang Wang, Xiangnan He:
GIF: A General Graph Unlearning Strategy via Influence Function. WWW 2023: 651-661 - [c153]Wentao Shi, Jiawei Chen, Fuli Feng, Jizhi Zhang, Junkang Wu, Chongming Gao, Xiangnan He:
On the Theories Behind Hard Negative Sampling for Recommendation. WWW 2023: 812-822 - [c152]Jiawei Chen, Junkang Wu, Jiancan Wu, Xuezhi Cao, Sheng Zhou, Xiangnan He:
Adap-τ : Adaptively Modulating Embedding Magnitude for Recommendation. WWW 2023: 1085-1096 - [c151]Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang:
Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum. WWW 2023: 1528-1538 - [i133]Wentao Shi, Jiawei Chen, Fuli Feng, Jizhi Zhang, Junkang Wu, Chongming Gao, Xiangnan He:
On the Theories Behind Hard Negative Sampling for Recommendation. CoRR abs/2302.03472 (2023) - [i132]Wentao Shi, Junkang Wu, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Wei Wu, Xiangnan He:
FFHR: Fully and Flexible Hyperbolic Representation for Knowledge Graph Completion. CoRR abs/2302.04088 (2023) - [i131]Minqi Jiang, Chaochuan Hou, Ao Zheng, Xiyang Hu, Songqiao Han, Hailiang Huang, Xiangnan He, Philip S. Yu, Yue Zhao:
Weakly Supervised Anomaly Detection: A Survey. CoRR abs/2302.04549 (2023) - [i130]Jiawei Chen, Junkang Wu, Jiancan Wu, Sheng Zhou, Xuezhi Cao, Xiangnan He:
Adap-tau: Adaptively Modulating Embedding Magnitude for Recommendation. CoRR abs/2302.04775 (2023) - [i129]Keqin Bao, Yu Wan, Dayiheng Liu, Baosong Yang, Wenqiang Lei, Xiangnan He, Derek F. Wong, Jun Xie:
Towards Fine-Grained Information: Identifying the Type and Location of Translation Errors. CoRR abs/2302.08975 (2023) - [i128]Zhicai Wang, Yanbin Hao, Tingting Mu, Ouxiang Li, Shuo Wang, Xiangnan He:
Bi-directional Distribution Alignment for Transductive Zero-Shot Learning. CoRR abs/2303.08698 (2023) - [i127]Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui, Xiang Wang, Xiangnan He:
GIF: A General Graph Unlearning Strategy via Influence Function. CoRR abs/2304.02835 (2023) - [i126]Wenjie Wang, Xinyu Lin, Fuli Feng, Xiangnan He, Tat-Seng Chua:
Generative Recommendation: Towards Next-generation Recommender Paradigm. CoRR abs/2304.03516 (2023) - [i125]Wenjie Wang, Yiyan Xu, Fuli Feng, Xinyu Lin, Xiangnan He, Tat-Seng Chua:
Diffusion Recommender Model. CoRR abs/2304.04971 (2023) - [i124]Yang Zhang, Tianhao Shi, Fuli Feng, Wenjie Wang, Dingxian Wang, Xiangnan He, Yongdong Zhang:
Reformulating CTR Prediction: Learning Invariant Feature Interactions for Recommendation. CoRR abs/2304.13643 (2023) - [i123]Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He:
TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation. CoRR abs/2305.00447 (2023) - [i122]Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He:
Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation. CoRR abs/2305.07609 (2023) - 2022
- [j51]Jiancan Wu, Xiangnan He, Xiang Wang, Qifan Wang, Weijian Chen, Jianxun Lian, Xing Xie:
Graph convolution machine for context-aware recommender system. Frontiers Comput. Sci. 16(6): 166614 (2022) - [j50]Yanfang Wang, Yongduo Sui, Xiang Wang, Zhenguang Liu, Xiangnan He:
Exploring lottery ticket hypothesis in media recommender systems. Int. J. Intell. Syst. 37(5): 3006-3024 (2022) - [j49]Richang Hong, Daqing Liu, Xiaoyu Mo, Xiangnan He, Hanwang Zhang:
Learning to Compose and Reason with Language Tree Structures for Visual Grounding. IEEE Trans. Pattern Anal. Mach. Intell. 44(2): 684-696 (2022) - [j48]Yuanyuan Jin, Wendi Ji, Wei Zhang, Xiangnan He, Xinyu Wang, Xiaoling Wang:
A KG-Enhanced Multi-Graph Neural Network for Attentive Herb Recommendation. IEEE ACM Trans. Comput. Biol. Bioinform. 19(5): 2560-2571 (2022) - [j47]Yanbin Hao, Shuo Wang, Pei Cao, Xinjian Gao, Tong Xu, Jinmeng Wu, Xiangnan He:
Attention in Attention: Modeling Context Correlation for Efficient Video Classification. IEEE Trans. Circuits Syst. Video Technol. 32(10): 7120-7132 (2022) - [j46]Yanbin Hao, Shuo Wang, Yi Tan, Xiangnan He, Zhenguang Liu, Meng Wang:
Spatio-Temporal Collaborative Module for Efficient Action Recognition. IEEE Trans. Image Process. 31: 7279-7291 (2022) - [j45]Chen Gao, Yong Li, Fuli Feng, Xiangning Chen, Kai Zhao, Xiangnan He, Depeng Jin:
Cross-domain Recommendation with Bridge-Item Embeddings. ACM Trans. Knowl. Discov. Data 16(1): 2:1-2:23 (2022) - [j44]Ming Gao, Xiangnan He, Leihui Chen, Tingting Liu, Jinglin Zhang, Aoying Zhou:
Learning Vertex Representations for Bipartite Networks. IEEE Trans. Knowl. Data Eng. 34(1): 379-393 (2022) - [j43]Bin Wu, Xiangnan He, Yun Chen, Liqiang Nie, Kai Zheng, Yangdong Ye:
Modeling Product's Visual and Functional Characteristics for Recommender Systems. IEEE Trans. Knowl. Data Eng. 34(3): 1330-1343 (2022) - [j42]Meng Wang, Weijie Fu, Xiangnan He, Shijie Hao, Xindong Wu:
A Survey on Large-Scale Machine Learning. IEEE Trans. Knowl. Data Eng. 34(6): 2574-2594 (2022) - [j41]Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, Jie Tang:
Modelling High-Order Social Relations for Item Recommendation. IEEE Trans. Knowl. Data Eng. 34(9): 4385-4397 (2022) - [j40]Yinwei Wei, Xiang Wang, Xiangnan He, Liqiang Nie, Yong Rui, Tat-Seng Chua:
Hierarchical User Intent Graph Network for Multimedia Recommendation. IEEE Trans. Multim. 24: 2701-2712 (2022) - [j39]Xiangnan He, Zhaochun Ren, Emine Yilmaz, Marc Najork, Tat-Seng Chua:
Graph Technologies for User Modeling and Recommendation: Introduction to the Special Issue - Part 1. ACM Trans. Inf. Syst. 40(2): 21:1-21:5 (2022) - [j38]Xiangnan He, Zhaochun Ren, Emine Yilmaz, Marc Najork, Tat-Seng Chua:
Introduction to the Special Section on Graph Technologies for User Modeling and Recommendation, Part 2. ACM Trans. Inf. Syst. 40(3): 42:1-42:5 (2022) - [c150]Moxin Li, Fuli Feng, Hanwang Zhang, Xiangnan He, Fengbin Zhu, Tat-Seng Chua:
Learning to Imagine: Integrating Counterfactual Thinking in Neural Discrete Reasoning. ACL (1) 2022: 57-69 - [c149]Chongming Gao, Shijun Li, Wenqiang Lei, Jiawei Chen, Biao Li, Peng Jiang, Xiangnan He, Jiaxin Mao, Tat-Seng Chua:
KuaiRec: A Fully-observed Dataset and Insights for Evaluating Recommender Systems. CIKM 2022: 540-550 - [c148]Chongming Gao, Shijun Li, Yuan Zhang, Jiawei Chen, Biao Li, Wenqiang Lei, Peng Jiang, Xiangnan He:
KuaiRand: An Unbiased Sequential Recommendation Dataset with Randomly Exposed Videos. CIKM 2022: 3953-3957 - [c147]Chao Huang, Lianghao Xia, Xiang Wang, Xiangnan He, Dawei Yin:
Self-Supervised Learning for Recommendation. CIKM 2022: 5136-5139 - [c146]Yanbin Hao, Hao Zhang, Chong-Wah Ngo, Xiangnan He:
Group Contextualization for Video Recognition. CVPR 2022: 918-928 - [c145]Chuhan Wu, Fangzhao Wu, Xiangnan He, Yongfeng Huang:
DebiasGAN: Eliminating Position Bias in News Recommendation with Adversarial Learning. EMNLP (Findings) 2022: 2933-2938 - [c144]Yingxin Wu, Xiang Wang, An Zhang, Xiangnan He, Tat-Seng Chua:
Discovering Invariant Rationales for Graph Neural Networks. ICLR 2022 - [c143]Sihang Li, Xiang Wang, An Zhang, Yingxin Wu, Xiangnan He, Tat-Seng Chua:
Let Invariant Rationale Discovery Inspire Graph Contrastive Learning. ICML 2022: 13052-13065 - [c142]Sihao Ding, Peng Wu, Fuli Feng, Yitong Wang, Xiangnan He, Yong Liao, Yongdong Zhang:
Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis. KDD 2022: 305-315 - [c141]Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua:
Causal Attention for Interpretable and Generalizable Graph Classification. KDD 2022: 1696-1705 - [c140]Xiaoyu Du, Zike Wu, Fuli Feng, Xiangnan He, Jinhui Tang:
Invariant Representation Learning for Multimedia Recommendation. ACM Multimedia 2022: 619-628 - [c139]Yanbin Hao, Jingru Duan, Hao Zhang, Bin Zhu, Pengyuan Zhou, Xiangnan He:
Unsupervised Video Hashing with Multi-granularity Contextualization and Multi-structure Preservation. ACM Multimedia 2022: 3754-3763 - [c138]Shuo Wang, Xinyu Zhang, Yanbin Hao, Chengbing Wang, Xiangnan He:
Multi-directional Knowledge Transfer for Few-Shot Learning. ACM Multimedia 2022: 3993-4002 - [c137]Yi Tan, Yanbin Hao, Hao Zhang, Shuo Wang, Xiangnan He:
Hierarchical Hourglass Convolutional Network for Efficient Video Classification. ACM Multimedia 2022: 5880-5891 - [c136]Zhicai Wang, Yanbin Hao, Xingyu Gao, Hao Zhang, Shuo Wang, Tingting Mu, Xiangnan He:
Parameterization of Cross-token Relations with Relative Positional Encoding for Vision MLP. ACM Multimedia 2022: 6288-6299 - [c135]Sihao Ding, Fuli Feng, Xiangnan He, Jinqiu Jin, Wenjie Wang, Yong Liao, Yongdong Zhang:
Interpolative Distillation for Unifying Biased and Debiased Recommendation. SIGIR 2022: 40-49 - [c134]Chao Huang, Xiang Wang, Xiangnan He, Dawei Yin:
Self-Supervised Learning for Recommender System. SIGIR 2022: 3440-3443 - [c133]Keqin Bao, Yu Wan, Dayiheng Liu, Baosong Yang, Wenqiang Lei, Xiangnan He, Derek F. Wong, Jun Xie:
Alibaba-Translate China's Submission for WMT 2022 Quality Estimation Shared Task. WMT 2022: 597-605 - [c132]Chen Gao, Xiang Wang, Xiangnan He, Yong Li:
Graph Neural Networks for Recommender System. WSDM 2022: 1623-1625 - [c131]Dian Cheng, Jiawei Chen, Wenjun Peng, Wenqin Ye, Fuyu Lv, Tao Zhuang, Xiaoyi Zeng, Xiangnan He:
IHGNN: Interactive Hypergraph Neural Network for Personalized Product Search. WWW 2022: 256-265 - [c130]Riccardo Tommasini, Senjuti Basu Roy, Xuan Wang, Hongwei Wang, Heng Ji, Jiawei Han, Preslav Nakov, Giovanni Da San Martino, Firoj Alam, Markus Schedl, Elisabeth Lex, Akash Bharadwaj, Graham Cormode, Milan Dojchinovski, Jan Forberg, Johannes Frey, Pieter Bonte, Marco Balduini, Matteo Belcao, Emanuele Della Valle, Junliang Yu, Hongzhi Yin, Tong Chen, Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Jamell Dacon, Lingjuan Lye, Jiliang Tang, Aristides Gionis, Stefan Neumann, Bruno Ordozgoiti, Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, Fabian M. Suchanek, Lingfei Wu, Yu Chen, Yunyao Li, Bang Liu, Filip Ilievski, Daniel Garijo, Hans Chalupsky, Pedro A. Szekely, Ilias Kanellos, Dimitris Sacharidis, Thanasis Vergoulis, Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy, Friedhelm Victor, Bernhard Haslhofer, George Katsogiannis-Meimarakis, Georgia Koutrika, Shengmin Jin, Danai Koutra, Reza Zafarani, Yulia Tsvetkov, Vidhisha Balachandran, Sachin Kumar, Xiangyu Zhao, Bo Chen, Huifeng Guo, Yejing Wang, Ruiming Tang, Yang Zhang, Wenjie Wang, Peng Wu, Fuli Feng, Xiangnan He:
Accepted Tutorials at The Web Conference 2022. WWW (Companion Volume) 2022: 391-399 - [c129]Yu Wang, Xin Xin, Zaiqiao Meng, Joemon M. Jose, Fuli Feng, Xiangnan He:
Learning Robust Recommenders through Cross-Model Agreement. WWW 2022: 2015-2025 - [c128]Qi Wan, Xiangnan He, Xiang Wang, Jiancan Wu, Wei Guo, Ruiming Tang:
Cross Pairwise Ranking for Unbiased Item Recommendation. WWW 2022: 2370-2378 - [c127]Wenjie Wang, Xinyu Lin, Fuli Feng, Xiangnan He, Min Lin, Tat-Seng Chua:
Causal Representation Learning for Out-of-Distribution Recommendation. WWW 2022: 3562-3571 - [r1]Yashar Deldjoo, Markus Schedl, Balázs Hidasi, Yinwei Wei, Xiangnan He:
Multimedia Recommender Systems: Algorithms and Challenges. Recommender Systems Handbook 2022: 973-1014 - [i121]Jiancan Wu, Xiang Wang, Xingyu Gao, Jiawei Chen, Hongcheng Fu, Tianyu Qiu, Xiangnan He:
On the Effectiveness of Sampled Softmax Loss for Item Recommendation. CoRR abs/2201.02327 (2022) - [i120]Ying-Xin Wu, Xiang Wang, An Zhang, Xia Hu, Fuli Feng, Xiangnan He, Tat-Seng Chua:
Deconfounding to Explanation Evaluation in Graph Neural Networks. CoRR abs/2201.08802 (2022) - [i119]Ying-Xin Wu, Xiang Wang, An Zhang, Xiangnan He, Tat-Seng Chua:
Discovering Invariant Rationales for Graph Neural Networks. CoRR abs/2201.12872 (2022) - [i118]Dian Cheng, Jiawei Chen, Wenjun Peng, Wenqin Ye, Fuyu Lv, Tao Zhuang, Xiaoyi Zeng, Xiangnan He:
IHGNN: Interactive Hypergraph Neural Network for Personalized Product Search. CoRR abs/2202.04972 (2022) - [i117]Chongming Gao, Shijun Li, Wenqiang Lei, Biao Li, Peng Jiang, Jiawei Chen, Xiangnan He, Jiaxin Mao, Tat-Seng Chua:
KuaiRec: A Fully-observed Dataset for Recommender Systems. CoRR abs/2202.10842 (2022) - [i116]Yanbin Hao, Hao Zhang, Chong-Wah Ngo, Xiangnan He:
Group Contextualization for Video Recognition. CoRR abs/2203.09694 (2022) - [i115]Chongming Gao, Wenqiang Lei, Jiawei Chen, Shiqi Wang, Xiangnan He, Shijun Li, Biao Li, Yuan Zhang, Peng Jiang:
CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System. CoRR abs/2204.01266 (2022) - [i114]Yuan Gao, Xiang Wang, Xiangnan He, Huamin Feng, Yongdong Zhang:
Rumor Detection with Self-supervised Learning on Texts and Social Graph. CoRR abs/2204.08838 (2022) - [i113]Yanbin Hao, Shuo Wang, Pei Cao, Xinjian Gao, Tong Xu, Jinmeng Wu, Xiangnan He:
Attention in Attention: Modeling Context Correlation for Efficient Video Classification. CoRR abs/2204.09303 (2022) - [i112]Xiang Wang, Ying-Xin Wu, An Zhang, Fuli Feng, Xiangnan He, Tat-Seng Chua:
Reinforced Causal Explainer for Graph Neural Networks. CoRR abs/2204.11028 (2022) - [i111]Qi Wan, Xiangnan He, Xiang Wang, Jiancan Wu, Wei Guo, Ruiming Tang:
Cross Pairwise Ranking for Unbiased Item Recommendation. CoRR abs/2204.12176 (2022) - [i110]Xiangnan He, Yang Zhang, Fuli Feng, Chonggang Song, Lingling Yi, Guohui Ling, Yongdong Zhang:
Addressing Confounding Feature Issue for Causal Recommendation. CoRR abs/2205.06532 (2022) - [i109]Xinyuan Zhu, Yang Zhang, Fuli Feng, Xun Yang, Dingxian Wang, Xiangnan He:
Mitigating Hidden Confounding Effects for Causal Recommendation. CoRR abs/2205.07499 (2022) - [i108]Jiajia Chen, Xin Xin, Xianfeng Liang, Xiangnan He, Jun Liu:
GDSRec: Graph-Based Decentralized Collaborative Filtering for Social Recommendation. CoRR abs/2205.09948 (2022) - [i107]Yu Wang, An Zhang, Xiang Wang, Xiangnan He, Tat-Seng Chua:
Differentiable Invariant Causal Discovery. CoRR abs/2205.15638 (2022) - [i106]Sihang Li, Xiang Wang, An Zhang, Yingxin Wu, Xiangnan He, Tat-Seng Chua:
Let Invariant Rationale Discovery Inspire Graph Contrastive Learning. CoRR abs/2206.07869 (2022) - [i105]Honglei Zhang, Fangyuan Luo, Jun Wu, Xiangnan He, Yidong Li:
LightFR: Lightweight Federated Recommendation with Privacy-preserving Matrix Factorization. CoRR abs/2206.11743 (2022) - [i104]Zhicai Wang, Yanbin Hao, Xingyu Gao, Hao Zhang, Shuo Wang, Tingting Mu, Xiangnan He:
Parameterization of Cross-Token Relations with Relative Positional Encoding for Vision MLP. CoRR abs/2207.07284 (2022) - [i103]Weijian Chen, Yixin Cao, Fuli Feng, Xiangnan He, Yongdong Zhang:
Explainable Sparse Knowledge Graph Completion via High-order Graph Reasoning Network. CoRR abs/2207.07503 (2022) - [i102]Chongming Gao, Shijun Li, Yuan Zhang, Jiawei Chen, Biao Li, Wenqiang Lei, Peng Jiang, Xiangnan He:
KuaiRand: An Unbiased Sequential Recommendation Dataset with Randomly Exposed Videos. CoRR abs/2208.08696 (2022) - [i101]Chen Gao, Yu Zheng, Wenjie Wang, Fuli Feng, Xiangnan He, Yong Li:
Causal Inference in Recommender Systems: A Survey and Future Directions. CoRR abs/2208.12397 (2022) - [i100]Chenxu Wang, Fuli Feng, Yang Zhang, Qifan Wang, Xunhan Hu, Xiangnan He:
Rethinking Missing Data: Aleatoric Uncertainty-Aware Recommendation. CoRR abs/2209.11679 (2022) - [i99]Kang Liu, Feng Xue, Xiangnan He, Dan Guo, Richang Hong:
Joint Multi-grained Popularity-aware Graph Convolution Collaborative Filtering for Recommendation. CoRR abs/2210.04614 (2022) - [i98]Keqin Bao, Yu Wan, Dayiheng Liu, Baosong Yang, Wenqiang Lei, Xiangnan He, Derek F. Wong, Jun Xie:
Alibaba-Translate China's Submission for WMT 2022 Quality Estimation Shared Task. CoRR abs/2210.10049 (2022) - [i97]Yongduo Sui, Xiang Wang, Jiancan Wu, An Zhang, Xiangnan He:
Adversarial Causal Augmentation for Graph Covariate Shift. CoRR abs/2211.02843 (2022) - [i96]Gang Chen, Jiawei Chen, Fuli Feng, Sheng Zhou, Xiangnan He:
Unbiased Knowledge Distillation for Recommendation. CoRR abs/2211.14729 (2022) - 2021
- [j37]Chongming Gao, Wenqiang Lei, Xiangnan He, Maarten de Rijke, Tat-Seng Chua:
Advances and challenges in conversational recommender systems: A survey. AI Open 2: 100-126 (2021) - [j36]Shunyu Jiang, Fuli Feng, Weijian Chen, Xiang Li, Xiangnan He:
Structure-enhanced meta-learning for few-shot graph classification. AI Open 2: 160-167 (2021) - [j35]Yeon-Chang Lee, Taeho Kim, Jaeho Choi, Xiangnan He, Sang-Wook Kim:
M-BPR: A novel approach to improving BPR for recommendation with multi-type pair-wise preferences. Inf. Sci. 547: 255-270 (2021) - [j34]Jingtao Ding, Guanghui Yu, Xiangnan He, Fuli Feng, Yong Li, Depeng Jin:
Sampler Design for Bayesian Personalized Ranking by Leveraging View Data. IEEE Trans. Knowl. Data Eng. 33(2): 667-681 (2021) - [j33]Da Cao, Xiangnan He, Lianhai Miao, Guangyi Xiao, Hao Chen, Jia Xu:
Social-Enhanced Attentive Group Recommendation. IEEE Trans. Knowl. Data Eng. 33(3): 1195-1209 (2021) - [j32]Fuli Feng, Xiangnan He, Jie Tang, Tat-Seng Chua:
Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure. IEEE Trans. Knowl. Data Eng. 33(6): 2493-2504 (2021) - [j31]Chen Gao, Xiangnan He, Dahua Gan, Xiangning Chen, Fuli Feng, Yong Li, Tat-Seng Chua, Lina Yao, Yang Song, Depeng Jin:
Learning to Recommend With Multiple Cascading Behaviors. IEEE Trans. Knowl. Data Eng. 33(6): 2588-2601 (2021) - [j30]Yaoyao Liu, Qianru Sun, Xiangnan He, An-An Liu, Yuting Su, Tat-Seng Chua:
Generating Face Images With Attributes for Free. IEEE Trans. Neural Networks Learn. Syst. 32(6): 2733-2743 (2021) - [j29]Jiawei Chen, Chengquan Jiang, Can Wang, Sheng Zhou, Yan Feng, Chun Chen, Martin Ester, Xiangnan He:
CoSam: An Efficient Collaborative Adaptive Sampler for Recommendation. ACM Trans. Inf. Syst. 39(3): 34:1-34:24 (2021) - [j28]Shijun Li, Wenqiang Lei, Qingyun Wu, Xiangnan He, Peng Jiang, Tat-Seng Chua:
Seamlessly Unifying Attributes and Items: Conversational Recommendation for Cold-start Users. ACM Trans. Inf. Syst. 39(4): 40:1-40:29 (2021) - [j27]Tong Xu, Peilun Zhou, Linkang Hu, Xiangnan He, Yao Hu, Enhong Chen:
Socializing the Videos: A Multimodal Approach for Social Relation Recognition. ACM Trans. Multim. Comput. Commun. Appl. 17(1): 23:1-23:23 (2021) - [j26]