Xiangnan He

According to our database, Xiangnan He authored at least 352 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

How graph convolutions amplify popularity bias for recommendation?

Jiajia Chen, Jiancan Wu, Jiawei Chen, Xin Xin, Yong Li, Xiangnan He

Frontiers Comput. Sci., October, 2024

Mitigating Hidden Confounding Effects for Causal Recommendation.

Xinyuan Zhu, Yang Zhang, Fuli Feng, Xun Yang, Dingxian Wang, Xiangnan He

IEEE Trans. Knowl. Data Eng., September, 2024

Revisiting Attack-Caused Structural Distribution Shift in Graph Anomaly Detection.

Yuan Gao, Jinghan Li, Xiang Wang, Xiangnan He, Huamin Feng, Yongdong Zhang

IEEE Trans. Knowl. Data Eng., September, 2024

Causal Inference in Recommender Systems: A Survey and Future Directions.

Chen Gao, Yu Zheng, Wenjie Wang, Fuli Feng, Xiangnan He, Yong Li

ACM Trans. Inf. Syst., July, 2024

Enhancing Out-of-distribution Generalization on Graphs via Causal Attention Learning.

Yongduo Sui, Wenyu Mao, Shuyao Wang, Xiang Wang, Jiancan Wu, Xiangnan He, Tat-Seng Chua

ACM Trans. Knowl. Discov. Data, June, 2024

Causal Incremental Graph Convolution for Recommender System Retraining.

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

IEEE Trans. Neural Networks Learn. Syst., April, 2024

Learning to Double-Check Model Prediction From a Causal Perspective.

Xun Deng, Fuli Feng, Xiang Wang, Xiangnan He, Hanwang Zhang, Tat-Seng Chua

IEEE Trans. Neural Networks Learn. Syst., April, 2024

CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System.

Chongming Gao, Shiqi Wang, Shijun Li, Jiawei Chen, Xiangnan He, Wenqiang Lei, Biao Li, Yuan Zhang, Peng Jiang

ACM Trans. Inf. Syst., January, 2024

Feature Mixture on Pre-Trained Model for Few-Shot Learning.

Shuo Wang, Jinda Lu, Haiyang Xu, Yanbin Hao, Xiangnan He

IEEE Trans. Image Process., 2024

Information Discovery in e-Commerce.

Zhaochun Ren, Xiangnan He, Dawei Yin, Maarten de Rijke

CoRR, 2024

AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models.

Junfeng Fang, Houcheng Jiang, Kun Wang, Yunshan Ma, Xiang Wang, Xiangnan He, Tat-Seng Chua

CoRR, 2024

Proactive Recommendation in Social Networks: Steering User Interest via Neighbor Influence.

Hang Pan, Shuxian Bi, Wenjie Wang, Haoxuan Li, Peng Wu, Fuli Feng, Xiangnan He

CoRR, 2024

Customizing Language Models with Instance-wise LoRA for Sequential Recommendation.

Xiaoyu Kong, Jiancan Wu, An Zhang, Leheng Sheng, Hui Lin, Xiang Wang, Xiangnan He

CoRR, 2024

Reinforced Prompt Personalization for Recommendation with Large Language Models.

Wenyu Mao, Jiancan Wu, Weijian Chen, Chongming Gao, Xiang Wang, Xiangnan He

CoRR, 2024

β-DPO: Direct Preference Optimization with Dynamic β.

Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He

CoRR, 2024

Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization.

Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jiawei Chen, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He

CoRR, 2024

Text-like Encoding of Collaborative Information in Large Language Models for Recommendation.

Yang Zhang, Keqin Bao, Ming Yang, Wenjie Wang, Fuli Feng, Xiangnan He

CoRR, 2024

A Survey of Generative Search and Recommendation in the Era of Large Language Models.

Yongqi Li, Xinyu Lin, Wenjie Wang, Fuli Feng, Liang Pang, Wenjie Li, Liqiang Nie, Xiangnan He, Tat-Seng Chua

CoRR, 2024

Exact and Efficient Unlearning for Large Language Model-based Recommendation.

Zhiyu Hu, Yang Zhang, Minghao Xiao, Wenjie Wang, Fuli Feng, Xiangnan He

CoRR, 2024

Enhancing Long-Term Recommendation with Bi-level Learnable Large Language Model Planning.

Wentao Shi, Xiangnan He, Yang Zhang, Chongming Gao, Xinyue Li, Jizhi Zhang, Qifan Wang, Fuli Feng

CoRR, 2024

DiFashion: Towards Personalized Outfit Generation and Recommendation.

Yiyan Xu, Wenjie Wang, Fuli Feng, Yunshan Ma, Jizhi Zhang, Xiangnan He

CoRR, 2024

EXGC: Bridging Efficiency and Explainability in Graph Condensation.

Junfeng Fang, Xinglin Li, Yongduo Sui, Yuan Gao, Guibin Zhang, Kun Wang, Xiang Wang, Xiangnan He

CoRR, 2024

Alleviating Structural Distribution Shift in Graph Anomaly Detection.

Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang

CoRR, 2024

Large Language Models for Recommendation: Progresses and Future Directions.

Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

The 2nd Workshop on Recommendation with Generative Models.

Wenjie Wang, Yang Zhang, Xinyu Lin, Fuli Feng, Weiwen Liu, Yong Liu, Xiangyu Zhao, Wayne Xin Zhao, Yang Song, Xiangnan He

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Lower-Left Partial AUC: An Effective and Efficient Optimization Metric for Recommendation.

Wentao Shi, Chenxu Wang, Fuli Feng, Yang Zhang, Wenjie Wang, Junkang Wu, Xiangnan He

Proceedings of the ACM on Web Conference 2024, 2024

Item-side Fairness of Large Language Model-based Recommendation System.

Meng Jiang, Keqin Bao, Jizhi Zhang, Wenjie Wang, Zhengyi Yang, Fuli Feng, Xiangnan He

Proceedings of the ACM on Web Conference 2024, 2024

Simulating Human Society with Large Language Model Agents: City, Social Media, and Economic System.

Chen Gao, Fengli Xu, Xu Chen, Xiang Wang, Xiangnan He, Yong Li

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

EXGC: Bridging Efficiency and Explainability in Graph Condensation.

Junfeng Fang, Xinglin Li, Yongduo Sui, Yuan Gao, Guibin Zhang, Kun Wang, Xiang Wang, Xiangnan He

Proceedings of the ACM on Web Conference 2024, 2024

Proactive Recommendation with Iterative Preference Guidance.

Shuxian Bi, Wenjie Wang, Hang Pan, Fuli Feng, Xiangnan He

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Leave No Patient Behind: Enhancing Medication Recommendation for Rare Disease Patients.

Zihao Zhao, Yi Jing, Fuli Feng, Jiancan Wu, Chongming Gao, Xiangnan He

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Diffusion Models for Generative Outfit Recommendation.

Yiyan Xu, Wenjie Wang, Fuli Feng, Yunshan Ma, Jizhi Zhang, Xiangnan He

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Fair Recommendations with Limited Sensitive Attributes: A Distributionally Robust Optimization Approach.

Tianhao Shi, Yang Zhang, Jizhi Zhang, Fuli Feng, Xiangnan He

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Large Language Models are Learnable Planners for Long-Term Recommendation.

Wentao Shi, Xiangnan He, Yang Zhang, Chongming Gao, Xinyue Li, Jizhi Zhang, Qifan Wang, Fuli Feng

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

LLaRA: Large Language-Recommendation Assistant.

Jiayi Liao, Sihang Li, Zhengyi Yang, Jiancan Wu, Yancheng Yuan, Xiang Wang, Xiangnan He

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

A3S: A General Active Clustering Method with Pairwise Constraints.

Xun Deng, Junlong Liu, Han Zhong, Fuli Feng, Chen Shen, Xiangnan He, Jieping Ye, Zheng Wang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference.

Haoxuan Li, Chunyuan Zheng, Sihao Ding, Peng Wu, Zhi Geng, Fuli Feng, Xiangnan He

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Towards 3D Molecule-Text Interpretation in Language Models.

Sihang Li, Zhiyuan Liu, Yanchen Luo, Xiang Wang, Xiangnan He, Kenji Kawaguchi, Tat-Seng Chua, Qi Tian

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Enhance Image Classification via Inter-Class Image Mixup with Diffusion Model.

Zhicai Wang, Longhui Wei, Tan Wang, Heyu Chen, Yanbin Hao, Xiang Wang, Xiangnan He, Qi Tian

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Preliminary Study on Incremental Learning for Large Language Model-based Recommender Systems.

Tianhao Shi, Yang Zhang, Zhijian Xu, Chong Chen, Fuli Feng, Xiangnan He, Qi Tian

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Text-like Encoding of Collaborative Information in Large Language Models for Recommendation.

Yang Zhang, Keqin Bao, Ming Yan, Wenjie Wang, Fuli Feng, Xiangnan He

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Boosting Few-Shot Learning via Attentive Feature Regularization.

Xingyu Zhu, Shuo Wang, Jinda Lu, Yanbin Hao, Haifeng Liu, Xiangnan He

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Text-to-Image Generation for Abstract Concepts.

Jiayi Liao, Xu Chen, Qiang Fu, Lun Du, Xiangnan He, Xiang Wang, Shi Han, Dongmei Zhang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

GCRec: Graph-Augmented Capsule Network for Next-Item Recommendation.

Bin Wu, Xiangnan He, Qi Zhang, Meng Wang, Yangdong Ye

IEEE Trans. Neural Networks Learn. Syst., December, 2023

Rethinking Missing Data: Aleatoric Uncertainty-Aware Recommendation.

Chenxu Wang, Fuli Feng, Yang Zhang, Qifan Wang, Xunhan Hu, Xiangnan He

IEEE Trans. Big Data, December, 2023

LightFR: Lightweight Federated Recommendation with Privacy-preserving Matrix Factorization.

Honglei Zhang, Fangyuan Luo, Jun Wu, Xiangnan He, Yidong Li

ACM Trans. Inf. Syst., October, 2023

Popularity Bias is not Always Evil: Disentangling Benign and Harmful Bias for Recommendation.

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

IEEE Trans. Knowl. Data Eng., October, 2023

Rumor detection with self-supervised learning on texts and social graph.

Yuan Gao, Xiang Wang, Xiangnan He, Huamin Feng, Yong-Dong Zhang

Frontiers Comput. Sci., August, 2023

Graph-Augmented Co-Attention Model for Socio-Sequential Recommendation.

Bin Wu, Xiangnan He, Le Wu, Xue Zhang, Yangdong Ye

IEEE Trans. Syst. Man Cybern. Syst., July, 2023

A Survey on Accuracy-Oriented Neural Recommendation: From Collaborative Filtering to Information-Rich Recommendation.

Le Wu, Xiangnan He, Xiang Wang, Kun Zhang, Meng Wang

IEEE Trans. Knowl. Data Eng., May, 2023

GDSRec: Graph-Based Decentralized Collaborative Filtering for Social Recommendation.

Jiajia Chen, Xin Xin, Xianfeng Liang, Xiangnan He, Jun Liu

IEEE Trans. Knowl. Data Eng., May, 2023

Time-aware Path Reasoning on Knowledge Graph for Recommendation.

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

ACM Trans. Inf. Syst., April, 2023

CatGCN: Graph Convolutional Networks With Categorical Node Features.

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

IEEE Trans. Knowl. Data Eng., April, 2023

A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions.

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

Trans. Recomm. Syst., March, 2023

User-Specific Adaptive Fine-Tuning for Cross-Domain Recommendations.

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

IEEE Trans. Knowl. Data Eng., March, 2023

Bundle Recommendation and Generation With Graph Neural Networks.

Jianxin Chang, Chen Gao, Xiangnan He, Depeng Jin, Yong Li

IEEE Trans. Knowl. Data Eng., March, 2023

Joint Multi-Grained Popularity-Aware Graph Convolution Collaborative Filtering for Recommendation.

Kang Liu, Feng Xue, Xiangnan He, Dan Guo, Richang Hong

IEEE Trans. Comput. Soc. Syst., February, 2023

Boosting Hyperspectral Image Classification with Dual Hierarchical Learning.

Shuo Wang, Huixia Ben, Yanbin Hao, Xiangnan He, Meng Wang

ACM Trans. Multim. Comput. Commun. Appl., January, 2023

Interactive active learning for fairness with partial group label.

Zeyu Yang, Jizhi Zhang, Fuli Feng, Chongming Gao, Qifan Wang, Xiangnan He

AI Open, January, 2023

Information Retrieval meets Large Language Models: A strategic report from Chinese IR community.

Qingyao Ai, Ting Bai, Zhao Cao, Yi Chang, Jiawei Chen, Zhumin Chen, Zhiyong Cheng, Shoubin Dong, Zhicheng Dou, Fuli Feng, Shen Gao, Jiafeng Guo, Xiangnan He, Yanyan Lan, Chenliang Li, Yiqun Liu, Ziyu Lyu, Weizhi Ma, Jun Ma, Zhaochun Ren, Pengjie Ren, Zhiqiang Wang, Mingwen Wang, Ji-Rong Wen, Le Wu, Xin Xin, Jun Xu, Dawei Yin, Peng Zhang, Fan Zhang, Weinan Zhang, Min Zhang, Xiaofei Zhu

AI Open, January, 2023

Bias and Debias in Recommender System: A Survey and Future Directions.

Jiawei Chen, Hande Dong, Xiang Wang, Fuli Feng, Meng Wang, Xiangnan He

ACM Trans. Inf. Syst., 2023

Addressing Confounding Feature Issue for Causal Recommendation.

Xiangnan He, Yang Zhang, Fuli Feng, Chonggang Song, Lingling Yi, Guohui Ling, Yongdong Zhang

ACM Trans. Inf. Syst., 2023

Incorporating Price into Recommendation With Graph Convolutional Networks.

Yu Zheng, Chen Gao, Xiangnan He, Depeng Jin, Yong Li

IEEE Trans. Knowl. Data Eng., 2023

Adversarial Attack on Large Scale Graph.

Jintang Li, Tao Xie, Liang Chen, Fenfang Xie, Xiangnan He, Zibin Zheng

IEEE Trans. Knowl. Data Eng., 2023

Cross-GCN: Enhancing Graph Convolutional Network with $k$k-Order Feature Interactions.

Fuli Feng, Xiangnan He, Hanwang Zhang, Tat-Seng Chua

IEEE Trans. Knowl. Data Eng., 2023

Reinforced Causal Explainer for Graph Neural Networks.

Xiang Wang, Yingxin Wu, An Zhang, Fuli Feng, Xiangnan He, Tat-Seng Chua

IEEE Trans. Pattern Anal. Mach. Intell., 2023

Preliminary Study on Incremental Learning for Large Language Model-based Recommender Systems.

Tianhao Shi, Yang Zhang, Zhijian Xu, Chong Chen, Fuli Feng, Xiangnan He, Qi Tian

CoRR, 2023

CAR: Consolidation, Augmentation and Regulation for Recipe Retrieval.

Fangzhou Song, Bin Zhu, Yanbin Hao, Shuo Wang, Xiangnan He

CoRR, 2023

Large Language Model Can Interpret Latent Space of Sequential Recommender.

Zhengyi Yang, Jiancan Wu, Yanchen Luo, Jizhi Zhang, Yancheng Yuan, An Zhang, Xiang Wang, Xiangnan He

CoRR, 2023

CoLLM: Integrating Collaborative Embeddings into Large Language Models for Recommendation.

Yang Zhang, Fuli Feng, Jizhi Zhang, Keqin Bao, Qifan Wang, Xiangnan He

CoRR, 2023

Model-enhanced Contrastive Reinforcement Learning for Sequential Recommendation.

Chengpeng Li, Zhengyi Yang, Jizhi Zhang, Jiancan Wu, Dingxian Wang, Xiangnan He, Xiang Wang

CoRR, 2023

A Content-Driven Micro-Video Recommendation Dataset at Scale.

Yongxin Ni, Yu Cheng, Xiangyan Liu, Junchen Fu, Youhua Li, Xiangnan He, Yongfeng Zhang, Fajie Yuan

CoRR, 2023

Selective Volume Mixup for Video Action Recognition.

Yi Tan, Zhaofan Qiu, Yanbin Hao, Ting Yao, Xiangnan He, Tao Mei

CoRR, 2023

Label Denoising through Cross-Model Agreement.

Yu Wang, Xin Xin, Zaiqiao Meng, Xiangnan He, Joemon M. Jose, Fuli Feng

CoRR, 2023

A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems.

Keqin Bao, Jizhi Zhang, Wenjie Wang, Yang Zhang, Zhengyi Yang, Yancheng Luo, Fuli Feng, Xiangnan He, Qi Tian

CoRR, 2023

Recommendation Unlearning via Influence Function.

Yang Zhang, Zhiyu Hu, Yimeng Bai, Fuli Feng, Jiancan Wu, Qifan Wang, Xiangnan He

CoRR, 2023

Embracing Uncertainty: Adaptive Vague Preference Policy Learning for Multi-round Conversational Recommendation.

Gangyi Zhang, Chongming Gao, Wenqiang Lei, Xiaojie Guo, Shijun Li, Lingfei Wu, Hongshen Chen, Zhuozhi Ding, Sulong Xu, Xiangnan He

CoRR, 2023

Generative Recommendation: Towards Next-generation Recommender Paradigm.

Wenjie Wang, Xinyu Lin, Fuli Feng, Xiangnan He, Tat-Seng Chua

CoRR, 2023

Towards Fine-Grained Information: Identifying the Type and Location of Translation Errors.

Keqin Bao, Yu Wan, Dayiheng Liu, Baosong Yang, Wenqiang Lei, Xiangnan He, Derek F. Wong, Jun Xie

CoRR, 2023

Adap-tau: Adaptively Modulating Embedding Magnitude for Recommendation.

Jiawei Chen, Junkang Wu, Jiancan Wu, Sheng Zhou, Xuezhi Cao, Xiangnan He

CoRR, 2023

Weakly Supervised Anomaly Detection: A Survey.

Minqi Jiang, Chaochuan Hou, Ao Zheng, Xiyang Hu, Songqiao Han, Hailiang Huang, Xiangnan He, Philip S. Yu, Yue Zhao

CoRR, 2023

FFHR: Fully and Flexible Hyperbolic Representation for Knowledge Graph Completion.

Wentao Shi, Junkang Wu, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Wei Wu, Xiangnan He

CoRR, 2023

GIF: A General Graph Unlearning Strategy via Influence Function.

Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui, Xiang Wang, Xiangnan He

Proceedings of the ACM Web Conference 2023, 2023

On the Theories Behind Hard Negative Sampling for Recommendation.

Wentao Shi, Jiawei Chen, Fuli Feng, Jizhi Zhang, Junkang Wu, Chongming Gao, Xiangnan He

Proceedings of the ACM Web Conference 2023, 2023

Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum.

Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang

Proceedings of the ACM Web Conference 2023, 2023

Adap-τ : Adaptively Modulating Embedding Magnitude for Recommendation.

Jiawei Chen, Junkang Wu, Jiancan Wu, Xuezhi Cao, Sheng Zhou, Xiangnan He

Proceedings of the ACM Web Conference 2023, 2023

Alleviating Structural Distribution Shift in Graph Anomaly Detection.

Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Cooperative Explanations of Graph Neural Networks.

Junfeng Fang, Xiang Wang, An Zhang, Zemin Liu, Xiangnan He, Tat-Seng Chua

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Unbiased Knowledge Distillation for Recommendation.

Gang Chen, Jiawei Chen, Fuli Feng, Sheng Zhou, Xiangnan He

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Reformulating CTR Prediction: Learning Invariant Feature Interactions for Recommendation.

Yang Zhang, Tianhao Shi, Fuli Feng, Wenjie Wang, Dingxian Wang, Xiangnan He, Yongdong Zhang

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

A Generic Learning Framework for Sequential Recommendation with Distribution Shifts.

Zhengyi Yang, Xiangnan He, Jizhi Zhang, Jiancan Wu, Xin Xin, Jiawei Chen, Xiang Wang

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Causal Recommendation: Progresses and Future Directions.

Wenjie Wang, Yang Zhang, Haoxuan Li, Peng Wu, Fuli Feng, Xiangnan He

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Diffusion Recommender Model.

Wenjie Wang, Yiyan Xu, Fuli Feng, Xinyu Lin, Xiangnan He, Tat-Seng Chua

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Alleviating Matthew Effect of Offline Reinforcement Learning in Interactive Recommendation.

Chongming Gao, Kexin Huang, Jiawei Chen, Yuan Zhang, Biao Li, Peng Jiang, Shiqi Wang, Zhong Zhang, Xiangnan He

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation.

Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

RecAD: Towards A Unified Library for Recommender Attack and Defense.

Changsheng Wang, Jianbai Ye, Wenjie Wang, Chongming Gao, Fuli Feng, Xiangnan He

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

ADRNet: A Generalized Collaborative Filtering Framework Combining Clinical and Non-Clinical Data for Adverse Drug Reaction Prediction.

Haoxuan Li, Taojun Hu, Zetong Xiong, Chunyuan Zheng, Fuli Feng, Xiangnan He, Xiao-Hua Zhou

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation.

Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion.

Zhengyi Yang, Jiancan Wu, Zhicai Wang, Xiang Wang, Yancheng Yuan, Xiangnan He

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Understanding Contrastive Learning via Distributionally Robust Optimization.

Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Xiang Wang, Xiangnan He

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift.

Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach.

Haoxuan Li, Kunhan Wu, Chunyuan Zheng, Yanghao Xiao, Hao Wang, Zhi Geng, Fuli Feng, Xiangnan He, Peng Wu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fairly Recommending with Social Attributes: A Flexible and Controllable Optimization Approach.

Jinqiu Jin, Haoxuan Li, Fuli Feng, Sihao Ding, Peng Wu, Xiangnan He

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis.

Junfeng Fang, Wei Liu, Yuan Gao, Zemin Liu, An Zhang, Xiang Wang, Xiangnan He

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

CgT-GAN: CLIP-guided Text GAN for Image Captioning.

Jiarui Yu, Haoran Li, Yanbin Hao, Bin Zhu, Tong Xu, Xiangnan He

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Semantic-based Selection, Synthesis, and Supervision for Few-shot Learning.

Jinda Lu, Shuo Wang, Xinyu Zhang, Yanbin Hao, Xiangnan He

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Discriminative-Invariant Representation Learning for Unbiased Recommendation.

Hang Pan, Jiawei Chen, Fuli Feng, Wentao Shi, Junkang Wu, Xiangnan He

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Modeling Product's Visual and Functional Characteristics for Recommender Systems (Extended Abstract).

Bin Wu, Xiangnan He, Yu Chen, Liqiang Nie, Kai Zheng, Yangdong Ye

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

LightMIRM: Light Meta-learned Invariant Risk Minimization for Trustworthy Loan Default Prediction.

Meng Jiang, Yang Zhang, Yuan Gao, Yansong Wang, Fuli Feng, Xiangnan He

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Modelling High-Order Social Relations for Item Recommendation (Extended Abstract).

Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, Jie Tang

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Attack Prompt Generation for Red Teaming and Defending Large Language Models.

Boyi Deng, Wenjie Wang, Fuli Feng, Yang Deng, Qifan Wang, Xiangnan He

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Bi-Directional Distribution Alignment for Transductive Zero-Shot Learning.

Zhicai Wang, Yanbin Hao, Tingting Mu, Ouxiang Li, Shuo Wang, Xiangnan He

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

The 1st Workshop on Recommendation with Generative Models.

Wenjie Wang, Yong Liu, Yang Zhang, Weiwen Liu, Fuli Feng, Xiangnan He, Aixin Sun

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

How Can Contrastive Pre-training Benefit Audio-Visual Segmentation? A Study from Supervised and Zero-shot Perspectives.

Jiarui Yu, Haoran Li, Yanbin Hao, Jinmeng Wu, Tong Xu, Shuo Wang, Xiangnan He

Proceedings of the 34th British Machine Vision Conference 2023, 2023

Counterfactual Active Learning for Out-of-Distribution Generalization.

Xun Deng, Wenjie Wang, Fuli Feng, Hanwang Zhang, Xiangnan He, Yong Liao

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Knowledge Graph Embedding by Normalizing Flows.

Changyi Xiao, Xiangnan He, Yixin Cao

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Multimedia Recommender Systems: Algorithms and Challenges.

Yashar Deldjoo, Markus Schedl, Balázs Hidasi, Yinwei Wei, Xiangnan He

Proceedings of the Recommender Systems Handbook, 2022

Introduction to the Special Section on Graph Technologies for User Modeling and Recommendation, Part 2.

Xiangnan He, Zhaochun Ren, Emine Yilmaz, Marc Najork, Tat-Seng Chua

ACM Trans. Inf. Syst., 2022

Graph Technologies for User Modeling and Recommendation: Introduction to the Special Issue - Part 1.

Xiangnan He, Zhaochun Ren, Emine Yilmaz, Marc Najork, Tat-Seng Chua

ACM Trans. Inf. Syst., 2022

Hierarchical User Intent Graph Network for Multimedia Recommendation.

Yinwei Wei, Xiang Wang, Xiangnan He, Liqiang Nie, Yong Rui, Tat-Seng Chua

IEEE Trans. Multim., 2022

Modeling Product's Visual and Functional Characteristics for Recommender Systems.

Bin Wu, Xiangnan He, Yun Chen, Liqiang Nie, Kai Zheng, Yangdong Ye

IEEE Trans. Knowl. Data Eng., 2022

A Survey on Large-Scale Machine Learning.

Meng Wang, Weijie Fu, Xiangnan He, Shijie Hao, Xindong Wu

IEEE Trans. Knowl. Data Eng., 2022

Modelling High-Order Social Relations for Item Recommendation.

Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, Jie Tang

IEEE Trans. Knowl. Data Eng., 2022

Learning Vertex Representations for Bipartite Networks.

Ming Gao, Xiangnan He, Leihui Chen, Tingting Liu, Jinglin Zhang, Aoying Zhou

IEEE Trans. Knowl. Data Eng., 2022

Cross-domain Recommendation with Bridge-Item Embeddings.

Chen Gao, Yong Li, Fuli Feng, Xiangning Chen, Kai Zhao, Xiangnan He, Depeng Jin

ACM Trans. Knowl. Discov. Data, 2022

Spatio-Temporal Collaborative Module for Efficient Action Recognition.

Yanbin Hao, Shuo Wang, Yi Tan, Xiangnan He, Zhenguang Liu, Meng Wang

IEEE Trans. Image Process., 2022

Attention in Attention: Modeling Context Correlation for Efficient Video Classification.

Yanbin Hao, Shuo Wang, Pei Cao, Xinjian Gao, Tong Xu, Jinmeng Wu, Xiangnan He

IEEE Trans. Circuits Syst. Video Technol., 2022

A KG-Enhanced Multi-Graph Neural Network for Attentive Herb Recommendation.

Yuanyuan Jin, Wendi Ji, Wei Zhang, Xiangnan He, Xinyu Wang, Xiaoling Wang

IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Learning to Compose and Reason with Language Tree Structures for Visual Grounding.

Richang Hong, Daqing Liu, Xiaoyu Mo, Xiangnan He, Hanwang Zhang

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Exploring lottery ticket hypothesis in media recommender systems.

Yanfang Wang, Yongduo Sui, Xiang Wang, Zhenguang Liu, Xiangnan He

Int. J. Intell. Syst., 2022

Graph convolution machine for context-aware recommender system.

Jiancan Wu, Xiangnan He, Xiang Wang, Qifan Wang, Weijian Chen, Jianxun Lian, Xing Xie

Frontiers Comput. Sci., 2022

Adversarial Causal Augmentation for Graph Covariate Shift.

Yongduo Sui, Xiang Wang, Jiancan Wu, An Zhang, Xiangnan He

CoRR, 2022

Explainable Sparse Knowledge Graph Completion via High-order Graph Reasoning Network.

Weijian Chen, Yixin Cao, Fuli Feng, Xiangnan He, Yongdong Zhang

CoRR, 2022

Differentiable Invariant Causal Discovery.

Yu Wang, An Zhang, Xiang Wang, Xiangnan He, Tat-Seng Chua

CoRR, 2022

Rumor Detection with Self-supervised Learning on Texts and Social Graph.

Yuan Gao, Xiang Wang, Xiangnan He, Huamin Feng, Yongdong Zhang

CoRR, 2022

KuaiRec: A Fully-observed Dataset for Recommender Systems.

Chongming Gao, Shijun Li, Wenqiang Lei, Biao Li, Peng Jiang, Jiawei Chen, Xiangnan He, Jiaxin Mao, Tat-Seng Chua

CoRR, 2022

Deconfounding to Explanation Evaluation in Graph Neural Networks.

Ying-Xin Wu, Xiang Wang, An Zhang, Xia Hu, Fuli Feng, Xiangnan He, Tat-Seng Chua

CoRR, 2022

On the Effectiveness of Sampled Softmax Loss for Item Recommendation.

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

CoRR, 2022

Learning Robust Recommenders through Cross-Model Agreement.

Yu Wang, Xin Xin, Zaiqiao Meng, Joemon M. Jose, Fuli Feng, Xiangnan He

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Causal Representation Learning for Out-of-Distribution Recommendation.

Wenjie Wang, Xinyu Lin, Fuli Feng, Xiangnan He, Min Lin, Tat-Seng Chua

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Cross Pairwise Ranking for Unbiased Item Recommendation.

Qi Wan, Xiangnan He, Xiang Wang, Jiancan Wu, Wei Guo, Ruiming Tang

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

IHGNN: Interactive Hypergraph Neural Network for Personalized Product Search.

Dian Cheng, Jiawei Chen, Wenjun Peng, Wenqin Ye, Fuyu Lv, Tao Zhuang, Xiaoyi Zeng, Xiangnan He

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Accepted Tutorials at The Web Conference 2022.

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

Proceedings of the Companion of The Web Conference 2022, Virtual Event / Lyon, France, April 25, 2022

Graph Neural Networks for Recommender System.

Chen Gao, Xiang Wang, Xiangnan He, Yong Li

Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Alibaba-Translate China's Submission for WMT 2022 Quality Estimation Shared Task.

Keqin Bao, Yu Wan, Dayiheng Liu, Baosong Yang, Wenqiang Lei, Xiangnan He, Derek F. Wong, Jun Xie

Proceedings of the Seventh Conference on Machine Translation, 2022

Self-Supervised Learning for Recommender System.

Chao Huang, Xiang Wang, Xiangnan He, Dawei Yin

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Interpolative Distillation for Unifying Biased and Debiased Recommendation.

Sihao Ding, Fuli Feng, Xiangnan He, Jinqiu Jin, Wenjie Wang, Yong Liao, Yongdong Zhang

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Parameterization of Cross-token Relations with Relative Positional Encoding for Vision MLP.

Zhicai Wang, Yanbin Hao, Xingyu Gao, Hao Zhang, Shuo Wang, Tingting Mu, Xiangnan He

Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Hierarchical Hourglass Convolutional Network for Efficient Video Classification.

Yi Tan, Yanbin Hao, Hao Zhang, Shuo Wang, Xiangnan He

Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Unsupervised Video Hashing with Multi-granularity Contextualization and Multi-structure Preservation.

Yanbin Hao, Jingru Duan, Hao Zhang, Bin Zhu, Pengyuan Zhou, Xiangnan He

Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Invariant Representation Learning for Multimedia Recommendation.

Xiaoyu Du, Zike Wu, Fuli Feng, Xiangnan He, Jinhui Tang

Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Multi-directional Knowledge Transfer for Few-Shot Learning.

Shuo Wang, Xinyu Zhang, Yanbin Hao, Chengbing Wang, Xiangnan He

Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Causal Attention for Interpretable and Generalizable Graph Classification.

Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis.

Sihao Ding, Peng Wu, Fuli Feng, Yitong Wang, Xiangnan He, Yong Liao, Yongdong Zhang

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Let Invariant Rationale Discovery Inspire Graph Contrastive Learning.

Sihang Li, Xiang Wang, An Zhang, Yingxin Wu, Xiangnan He, Tat-Seng Chua

Proceedings of the International Conference on Machine Learning, 2022

Discovering Invariant Rationales for Graph Neural Networks.

Yingxin Wu, Xiang Wang, An Zhang, Xiangnan He, Tat-Seng Chua

Proceedings of the Tenth International Conference on Learning Representations, 2022

DebiasGAN: Eliminating Position Bias in News Recommendation with Adversarial Learning.

Chuhan Wu, Fangzhao Wu, Xiangnan He, Yongfeng Huang

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Group Contextualization for Video Recognition.

Yanbin Hao, Hao Zhang, Chong-Wah Ngo, Xiangnan He

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Self-Supervised Learning for Recommendation.

Chao Huang, Lianghao Xia, Xiang Wang, Xiangnan He, Dawei Yin

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

KuaiRand: An Unbiased Sequential Recommendation Dataset with Randomly Exposed Videos.

Chongming Gao, Shijun Li, Yuan Zhang, Jiawei Chen, Biao Li, Wenqiang Lei, Peng Jiang, Xiangnan He

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

KuaiRec: A Fully-observed Dataset and Insights for Evaluating Recommender Systems.

Chongming Gao, Shijun Li, Wenqiang Lei, Jiawei Chen, Biao Li, Peng Jiang, Xiangnan He, Jiaxin Mao, Tat-Seng Chua

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Learning to Imagine: Integrating Counterfactual Thinking in Neural Discrete Reasoning.

Moxin Li, Fuli Feng, Hanwang Zhang, Xiangnan He, Fengbin Zhu, Tat-Seng Chua

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Visually aware recommendation with aesthetic features.

Wenhui Yu, Xiangnan He, Jian Pei, Xu Chen, Li Xiong, Jinfei Liu, Zheng Qin

VLDB J., 2021

Socializing the Videos: A Multimodal Approach for Social Relation Recognition.

Tong Xu, Peilun Zhou, Linkang Hu, Xiangnan He, Yao Hu, Enhong Chen

ACM Trans. Multim. Comput. Commun. Appl., 2021

Seamlessly Unifying Attributes and Items: Conversational Recommendation for Cold-start Users.

Shijun Li, Wenqiang Lei, Qingyun Wu, Xiangnan He, Peng Jiang, Tat-Seng Chua

ACM Trans. Inf. Syst., 2021

CoSam: An Efficient Collaborative Adaptive Sampler for Recommendation.

Jiawei Chen, Chengquan Jiang, Can Wang, Sheng Zhou, Yan Feng, Chun Chen, Martin Ester, Xiangnan He

ACM Trans. Inf. Syst., 2021

Generating Face Images With Attributes for Free.

Yaoyao Liu, Qianru Sun, Xiangnan He, An-An Liu, Yuting Su, Tat-Seng Chua

IEEE Trans. Neural Networks Learn. Syst., 2021

Learning to Recommend With Multiple Cascading Behaviors.

Chen Gao, Xiangnan He, Dahua Gan, Xiangning Chen, Fuli Feng, Yong Li, Tat-Seng Chua, Lina Yao, Yang Song, Depeng Jin

IEEE Trans. Knowl. Data Eng., 2021

Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure.

Fuli Feng, Xiangnan He, Jie Tang, Tat-Seng Chua

IEEE Trans. Knowl. Data Eng., 2021

Sampler Design for Bayesian Personalized Ranking by Leveraging View Data.

Jingtao Ding, Guanghui Yu, Xiangnan He, Fuli Feng, Yong Li, Depeng Jin

IEEE Trans. Knowl. Data Eng., 2021

Social-Enhanced Attentive Group Recommendation.

Da Cao, Xiangnan He, Lianhai Miao, Guangyi Xiao, Hao Chen, Jia Xu

IEEE Trans. Knowl. Data Eng., 2021

M-BPR: A novel approach to improving BPR for recommendation with multi-type pair-wise preferences.

Yeon-Chang Lee, Taeho Kim, Jaeho Choi, Xiangnan He, Sang-Wook Kim

Inf. Sci., 2021

Deconfounded Training for Graph Neural Networks.

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

CoRR, 2021

Learning Robust Recommender from Noisy Implicit Feedback.

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

CoRR, 2021

GRCN: Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback.

Yinwei Wei, Xiang Wang, Liqiang Nie, Xiangnan He, Tat-Seng Chua

CoRR, 2021

Hierarchical User Intent Graph Network forMultimedia Recommendation.

Yinwei Wei, Xiang Wang, Xiangnan He, Liqiang Nie, Yong Rui, Tat-Seng Chua

CoRR, 2021

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

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

CoRR, 2021

Probabilistic and Variational Recommendation Denoising.

Yu Wang, Xin Xin, Zaiqiao Meng, Xiangnan He, Joemon M. Jose, Fuli Feng

CoRR, 2021

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

Le Wu, Xiangnan He, Xiang Wang, Kun Zhang, Meng Wang

CoRR, 2021

Structure-enhanced meta-learning for few-shot graph classification.

Shunyu Jiang, Fuli Feng, Weijian Chen, Xiang Li, Xiangnan He

AI Open, 2021

Advances and challenges in conversational recommender systems: A survey.

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

AI Open, 2021

Disentangling User Interest and Conformity for Recommendation with Causal Embedding.

Yu Zheng, Chen Gao, Xiang Li, Xiangnan He, Yong Li, Depeng Jin

Proceedings of the WWW '21: The Web Conference 2021, 2021

Learning Intents behind Interactions with Knowledge Graph for Recommendation.

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

Proceedings of the WWW '21: The Web Conference 2021, 2021

On the Equivalence of Decoupled Graph Convolution Network and Label Propagation.

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

Proceedings of the WWW '21: The Web Conference 2021, 2021

Denoising Implicit Feedback for Recommendation.

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

Proceedings of the WSDM '21, 2021

Causal Intervention for Leveraging Popularity Bias in Recommendation.

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

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Self-supervised Graph Learning for Recommendation.

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

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Clicks can be Cheating: Counterfactual Recommendation for Mitigating Clickbait Issue.

Wenjie Wang, Fuli Feng, Xiangnan He, Hanwang Zhang, Tat-Seng Chua

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Should Graph Convolution Trust Neighbors? A Simple Causal Inference Method.

Fuli Feng, Weiran Huang, Xiangnan He, Xin Xin, Qifan Wang, Tat-Seng Chua

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

AutoDebias: Learning to Debias for Recommendation.

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

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Bias Issues and Solutions in Recommender System: Tutorial on the RecSys 2021.

Jiawei Chen, Xiang Wang, Fuli Feng, Xiangnan He

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

Towards Multi-Grained Explainability for Graph Neural Networks.

Xiang Wang, Ying-Xin Wu, An Zhang, Xiangnan He, Tat-Seng Chua

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Selective Dependency Aggregation for Action Classification.

Yi Tan, Yanbin Hao, Xiangnan He, Yinwei Wei, Xun Yang

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System.

Tianxin Wei, Fuli Feng, Jiawei Chen, Ziwei Wu, Jinfeng Yi, Xiangnan He

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Deconfounded Recommendation for Alleviating Bias Amplification.

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

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Graph Learning based Recommender Systems: A Review.

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

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

On Disambiguating Authors: Collaboration Network Reconstruction in a Bottom-up Manner.

Na Li, Renyu Zhu, Xiaoxu Zhou, Xiangnan He, Wenyuan Cai, Ming Gao, Aoying Zhou

Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

Time horizon-aware modeling of financial texts for stock price prediction.

Fuli Feng, Xiang Wang, Xiangnan He, Ritchie Ng, Tat-Seng Chua

Proceedings of the ICAIF'21: 2nd ACM International Conference on AI in Finance, Virtual Event, November 3, 2021

DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network.

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

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

A Deep Learning Framework for Self-evolving Hierarchical Community Detection.

Daizong Ding, Mi Zhang, Hanrui Wang, Xudong Pan, Min Yang, Xiangnan He

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Empowering Language Understanding with Counterfactual Reasoning.

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

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020

Learning Visual Elements of Images for Discovery of Brand Posts.

Francesco Gelli, Tiberio Uricchio, Xiangnan He, Alberto Del Bimbo, Tat-Seng Chua

ACM Trans. Multim. Comput. Commun. Appl., 2020

Improving Implicit Recommender Systems with Auxiliary Data.

Jingtao Ding, Guanghui Yu, Yong Li, Xiangnan He, Depeng Jin

ACM Trans. Inf. Syst., 2020

Fast Matrix Factorization With Nonuniform Weights on Missing Data.

Xiangnan He, Jinhui Tang, Xiaoyu Du, Richang Hong, Tongwei Ren, Tat-Seng Chua

IEEE Trans. Neural Networks Learn. Syst., 2020

Knowledge-Based Topic Model for Multi-Modal Social Event Analysis.

Feng Xue, Richang Hong, Xiangnan He, Jianwei Wang, Shengsheng Qian, Changsheng Xu

IEEE Trans. Multim., 2020

Hierarchical Attention Network for Visually-Aware Food Recommendation.

Xiaoyan Gao, Fuli Feng, Xiangnan He, Heyan Huang, Xinyu Guan, Chong Feng, Zhaoyan Ming, Tat-Seng Chua

IEEE Trans. Multim., 2020

Adversarial Training Towards Robust Multimedia Recommender System.

Jinhui Tang, Xiaoyu Du, Xiangnan He, Fajie Yuan, Qi Tian, Tat-Seng Chua

IEEE Trans. Knowl. Data Eng., 2020

Generative Adversarial Active Learning for Unsupervised Outlier Detection.

Ye-Zheng Liu, Zhe Li, Chong Zhou, Yuanchun Jiang, Jianshan Sun, Meng Wang, Xiangnan He

IEEE Trans. Knowl. Data Eng., 2020

ATM: An Attentive Translation Model for Next-Item Recommendation.

Bin Wu, Xiangnan He, Zhongchuan Sun, Liang Chen, Yangdong Ye

IEEE Trans. Ind. Informatics, 2020

Report on the international workshop on natural language processing for recommendations (NLP4REC 2020) workshop held at WSDM 2020.

Xiao Huang, Pengjie Ren, Zhaochun Ren, Fei Sun, Xiangnan He, Dawei Yin, Maarten de Rijke

SIGIR Forum, 2020

Video-based recipe retrieval.

Da Cao, Ning Han, Hao Chen, Xiaochi Wei, Xiangnan He

Inf. Sci., 2020

MGAT: Multimodal Graph Attention Network for Recommendation.

Zhulin Tao, Yinwei Wei, Xiang Wang, Xiangnan He, Xianglin Huang, Tat-Seng Chua

Inf. Process. Manag., 2020

HoAFM: A High-order Attentive Factorization Machine for CTR Prediction.

Zhulin Tao, Xiang Wang, Xiangnan He, Xianglin Huang, Tat-Seng Chua

Inf. Process. Manag., 2020

Deep Learning for Matching in Search and Recommendation.

Jun Xu, Xiangnan He, Hang Li

Found. Trends Inf. Retr., 2020

Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System.

Tianxin Wei, Fuli Feng, Jiawei Chen, Chufeng Shi, Ziwei Wu, Jinfeng Yi, Xiangnan He

CoRR, 2020

Should Graph Convolution Trust Neighbors? A Simple Causal Inference Method.

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

CoRR, 2020

One Person, One Model, One World: Learning Continual User Representation without Forgetting.

Fajie Yuan, Guoxiao Zhang, Alexandros Karatzoglou, Xiangnan He, Joemon M. Jose, Beibei Kong, Yudong Li

CoRR, 2020

"Click" Is Not Equal to "Like": Counterfactual Recommendation for Mitigating Clickbait Issue.

Wenjie Wang, Fuli Feng, Xiangnan He, Hanwang Zhang, Tat-Seng Chua

CoRR, 2020

Data Augmentation View on Graph Convolutional Network and the Proposal of Monte Carlo Graph Learning.

Hande Dong, Zhaolin Ding, Xiangnan He, Fuli Feng, Shuxian Bi

CoRR, 2020

Disentangling User Interest and Popularity Bias for Recommendation with Causal Embedding.

Yu Zheng, Chen Gao, Xiang Li, Xiangnan He, Yong Li, Depeng Jin

CoRR, 2020

Graph Learning Approaches to Recommender Systems: A Review.

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

CoRR, 2020

A Survey of Adversarial Learning on Graphs.

Liang Chen, Jintang Li, Jiaying Peng, Tao Xie, Zengxu Cao, Kun Xu, Xiangnan He, Zibin Zheng

CoRR, 2020

Cross-GCN: Enhancing Graph Convolutional Network with k-Order Feature Interactions.

Fuli Feng, Xiangnan He, Hanwang Zhang, Tat-Seng Chua

CoRR, 2020

Bilinear Graph Neural Network with Node Interactions.

Hongmin Zhu, Fuli Feng, Xiangnan He, Xiang Wang, Yan Li, Kai Zheng, Yongdong Zhang

CoRR, 2020

Graph Convolution Machine for Context-aware Recommender System.

Jiancan Wu, Xiangnan He, Xiang Wang, Qifan Wang, Weijian Chen, Jianxun Lian, Xing Xie, Yongdong Zhang

CoRR, 2020

Parameter-Efficient Transfer from Sequential Behaviors for User Profiling and Recommendation.

Fajie Yuan, Xiangnan He, Alexandros Karatzoglou, Liguang Zhang

CoRR, 2020

Future Data Helps Training: Modeling Future Contexts for Session-based Recommendation.

Fajie Yuan, Xiangnan He, Haochuan Jiang, Guibing Guo, Jian Xiong, Zhezhao Xu, Yilin Xiong

Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Reinforced Negative Sampling over Knowledge Graph for Recommendation.

Xiang Wang, Yaokun Xu, Xiangnan He, Yixin Cao, Meng Wang, Tat-Seng Chua

Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

NLP4REC: The WSDM 2020 Workshop on Natural Language Processing for Recommendations.

Pengjie Ren, Zhaochun Ren, Fei Sun, Xiangnan He, Dawei Yin, Maarten de Rijke

Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Estimation-Action-Reflection: Towards Deep Interaction Between Conversational and Recommender Systems.

Wenqiang Lei, Xiangnan He, Yisong Miao, Qingyun Wu, Richang Hong, Min-Yen Kan, Tat-Seng Chua

Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

How to Retrain Recommender System?: A Sequential Meta-Learning Method.

Yang Zhang, Fuli Feng, Chenxu Wang, Xiangnan He, Meng Wang, Yan Li, Yongdong Zhang

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation.

Fajie Yuan, Xiangnan He, Alexandros Karatzoglou, Liguang Zhang

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Disentangled Graph Collaborative Filtering.

Xiang Wang, Hongye Jin, An Zhang, Xiangnan He, Tong Xu, Tat-Seng Chua

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Certifiable Robustness to Discrete Adversarial Perturbations for Factorization Machines.

Yang Liu, Xianzhuo Xia, Liang Chen, Xiangnan He, Carl Yang, Zibin Zheng

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Hierarchical Fashion Graph Network for Personalized Outfit Recommendation.

Xingchen Li, Xiang Wang, Xiangnan He, Long Chen, Jun Xiao, Tat-Seng Chua

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Conversational Recommendation: Formulation, Methods, and Evaluation.

Wenqiang Lei, Xiangnan He, Maarten de Rijke, Tat-Seng Chua

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Multi-behavior Recommendation with Graph Convolutional Networks.

Bowen Jin, Chen Gao, Xiangnan He, Depeng Jin, Yong Li

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Modeling Personalized Item Frequency Information for Next-basket Recommendation.

Haoji Hu, Xiangnan He, Jinyang Gao, Zhi-Li Zhang

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

FinIR 2020: The First Workshop on Information Retrieval in Finance.

Fuli Feng, Cheng Luo, Xiangnan He, Yiqun Liu, Tat-Seng Chua

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Bundle Recommendation with Graph Convolutional Networks.

Jianxin Chang, Chen Gao, Xiangnan He, Depeng Jin, Yong Li

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation.

Xiangnan He, Kuan Deng, Xiang Wang, Yan Li, Yong-Dong Zhang, Meng Wang

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback.

Yinwei Wei, Xiang Wang, Liqiang Nie, Xiangnan He, Tat-Seng Chua

Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020

Heterogeneous Fusion of Semantic and Collaborative Information for Visually-Aware Food Recommendation.

Lei Meng, Fuli Feng, Xiangnan He, Xiaoyan Gao, Tat-Seng Chua

Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020

How to Learn Item Representation for Cold-Start Multimedia Recommendation?

Xiaoyu Du, Xiang Wang, Xiangnan He, Zechao Li, Jinhui Tang, Tat-Seng Chua

Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020

STRONG: Spatio-Temporal Reinforcement Learning for Cross-Modal Video Moment Localization.

Da Cao, Yawen Zeng, Meng Liu, Xiangnan He, Meng Wang, Zheng Qin

Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020

Interactive Path Reasoning on Graph for Conversational Recommendation.

Wenqiang Lei, Gangyi Zhang, Xiangnan He, Yisong Miao, Xiang Wang, Liang Chen, Tat-Seng Chua

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Enterprise Cooperation and Competition Analysis with a Sign-Oriented Preference Network.

Le Dai, Yu Yin, Chuan Qin, Tong Xu, Xiangnan He, Enhong Chen, Hui Xiong

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Bilinear Graph Neural Network with Neighbor Interactions.

Hongmin Zhu, Fuli Feng, Xiangnan He, Xiang Wang, Yan Li, Kai Zheng, Yongdong Zhang

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Fast Adaptation for Cold-start Collaborative Filtering with Meta-learning.

Tianxin Wei, Ziwei Wu, Ruirui Li, Ziniu Hu, Fuli Feng, Xiangnan He, Yizhou Sun, Wei Wang

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Modeling Personalized Out-of-Town Distances in Location Recommendation.

Daizong Ding, Mi Zhang, Xudong Pan, Min Yang, Xiangnan He

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Price-aware Recommendation with Graph Convolutional Networks.

Yu Zheng, Chen Gao, Xiangnan He, Yong Li, Depeng Jin

Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

Improving Neural Relation Extraction with Implicit Mutual Relations.

Jun Kuang, Yixin Cao, Jianbing Zheng, Xiangnan He, Ming Gao, Aoying Zhou

Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

Syndrome-aware Herb Recommendation with Multi-Graph Convolution Network.

Yuanyuan Jin, Wei Zhang, Xiangnan He, Xinyu Wang, Xiaoling Wang

Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

Mining Unfollow Behavior in Large-Scale Online Social Networks via Spatial-Temporal Interaction.

Haozhe Wu, Zhiyuan Hu, Jia Jia, Yaohua Bu, Xiangnan He, Tat-Seng Chua

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Improving the Robustness of Wasserstein Embedding by Adversarial PAC-Bayesian Learning.

Daizong Ding, Mi Zhang, Xudong Pan, Min Yang, Xiangnan He

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Deep Item-based Collaborative Filtering for Top-N Recommendation.

Feng Xue, Xiangnan He, Xiang Wang, Jiandong Xu, Kai Liu, Richang Hong

ACM Trans. Inf. Syst., 2019

Attentive Aspect Modeling for Review-Aware Recommendation.

Xinyu Guan, Zhiyong Cheng, Xiangnan He, Yongfeng Zhang, Zhibo Zhu, Qinke Peng, Tat-Seng Chua

ACM Trans. Inf. Syst., 2019

Temporal Relational Ranking for Stock Prediction.

Fuli Feng, Xiangnan He, Xiang Wang, Cheng Luo, Yiqun Liu, Tat-Seng Chua

ACM Trans. Inf. Syst., 2019

Modeling Embedding Dimension Correlations via Convolutional Neural Collaborative Filtering.

Xiaoyu Du, Xiangnan He, Fajie Yuan, Jinhui Tang, Zhiguang Qin, Tat-Seng Chua

ACM Trans. Inf. Syst., 2019

Special issue on multimedia recommendation and multi-modal data analysis.

Xiangnan He, Zhenguang Liu, Hanwang Zhang, Chong-Wah Ngo, Svebor Karaman, Yongfeng Zhang

Multim. Syst., 2019

Modeling the Past and Future Contexts for Session-based Recommendation.

Fajie Yuan, Xiangnan He, Guibing Guo, Zhezhao Xu, Jian Xiong, Xiuqiang He

CoRR, 2019

LambdaOpt: Learn to Regularize Recommender Models in Finer Levels.

Yihong Chen, Bei Chen, Xiangnan He, Chen Gao, Yong Li, Jian-Guang Lou, Yue Wang

CoRR, 2019

Learning Vertex Representations for Bipartite Networks.

Ming Gao, Xiangnan He, Leihui Chen, Aoying Zhou

CoRR, 2019

Cross-domain Recommendation Without Sharing User-relevant Data.

Chen Gao, Xiangning Chen, Fuli Feng, Kai Zhao, Xiangnan He, Yong Li, Depeng Jin

Proceedings of the World Wide Web Conference, 2019

Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preferences.

Yixin Cao, Xiang Wang, Xiangnan He, Zikun Hu, Tat-Seng Chua

Proceedings of the World Wide Web Conference, 2019

A Simple Convolutional Generative Network for Next Item Recommendation.

Fajie Yuan, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M. Jose, Xiangnan He

Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019

Interpretable Fashion Matching with Rich Attributes.

Xun Yang, Xiangnan He, Xiang Wang, Yunshan Ma, Fuli Feng, Meng Wang, Tat-Seng Chua

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

Relational Collaborative Filtering: Modeling Multiple Item Relations for Recommendation.

Xin Xin, Xiangnan He, Yongfeng Zhang, Yongdong Zhang, Joemon M. Jose

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

Neural Graph Collaborative Filtering.

Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng, Tat-Seng Chua

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

MMGCN: Multi-modal Graph Convolution Network for Personalized Recommendation of Micro-video.

Yinwei Wei, Xiang Wang, Liqiang Nie, Xiangnan He, Richang Hong, Tat-Seng Chua

Proceedings of the 27th ACM International Conference on Multimedia, 2019

Learning Subjective Attributes of Images from Auxiliary Sources.

Francesco Gelli, Tiberio Uricchio, Xiangnan He, Alberto Del Bimbo, Tat-Seng Chua

Proceedings of the 27th ACM International Conference on Multimedia, 2019

Mixed-dish Recognition with Contextual Relation Networks.

Lixi Deng, Jingjing Chen, Qianru Sun, Xiangnan He, Sheng Tang, Zhaoyan Ming, Yongdong Zhang, Tat-Seng Chua

Proceedings of the 27th ACM International Conference on Multimedia, 2019

KGAT: Knowledge Graph Attention Network for Recommendation.

Xiang Wang, Xiangnan He, Yixin Cao, Meng Liu, Tat-Seng Chua

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Sets2Sets: Learning from Sequential Sets with Neural Networks.

Haoji Hu, Xiangnan He

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Modeling Extreme Events in Time Series Prediction.

Daizong Ding, Mi Zhang, Xudong Pan, Min Yang, Xiangnan He

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

λOpt: Learn to Regularize Recommender Models in Finer Levels.

Yihong Chen, Bei Chen, Xiangnan He, Chen Gao, Yong Li, Jian-Guang Lou, Yue Wang

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

CFM: Convolutional Factorization Machines for Context-Aware Recommendation.

Xin Xin, Bo Chen, Xiangnan He, Dong Wang, Yue Ding, Joemon M. Jose

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Enhancing Stock Movement Prediction with Adversarial Training.

Fuli Feng, Huimin Chen, Xiangnan He, Ji Ding, Maosong Sun, Tat-Seng Chua

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Reinforced Negative Sampling for Recommendation with Exposure Data.

Jingtao Ding, Yuhan Quan, Xiangnan He, Yong Li, Depeng Jin

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Matching User with Item Set: Collaborative Bundle Recommendation with Deep Attention Network.

Liang Chen, Yang Liu, Xiangnan He, Lianli Gao, Zibin Zheng

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Semi-supervised User Profiling with Heterogeneous Graph Attention Networks.

Weijian Chen, Yulong Gu, Zhaochun Ren, Xiangnan He, Hongtao Xie, Tong Guo, Dawei Yin, Yongdong Zhang

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Neural Multi-task Recommendation from Multi-behavior Data.

Chen Gao, Xiangnan He, Dahua Gan, Xiangning Chen, Fuli Feng, Yong Li, Tat-Seng Chua, Depeng Jin

Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

Counterfactual Critic Multi-Agent Training for Scene Graph Generation.

Long Chen, Hanwang Zhang, Jun Xiao, Xiangnan He, Shiliang Pu, Shih-Fu Chang

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Learning and Reasoning on Graph for Recommendation.

Xiang Wang, Xiangnan He, Tat-Seng Chua

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Explainable Reasoning over Knowledge Graphs for Recommendation.

Xiang Wang, Dingxian Wang, Canran Xu, Xiangnan He, Yixin Cao, Tat-Seng Chua

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering.

Xiangpeng Li, Jingkuan Song, Lianli Gao, Xianglong Liu, Wenbing Huang, Xiangnan He, Chuang Gan

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Attributed Social Network Embedding.

Lizi Liao, Xiangnan He, Hanwang Zhang, Tat-Seng Chua

IEEE Trans. Knowl. Data Eng., 2018

NAIS: Neural Attentive Item Similarity Model for Recommendation.

Xiangnan He, Zhankui He, Jingkuan Song, Zhenguang Liu, Yu-Gang Jiang, Tat-Seng Chua

IEEE Trans. Knowl. Data Eng., 2018

Scene Dynamics: Counterfactual Critic Multi-Agent Training for Scene Graph Generation.

Long Chen, Hanwang Zhang, Jun Xiao, Xiangnan He, Shiliang Pu, Shih-Fu Chang

CoRR, 2018

Fast Matrix Factorization with Non-Uniform Weights on Missing Data.

Xiangnan He, Jinhui Tang, Xiaoyu Du, Richang Hong, Tongwei Ren, Tat-Seng Chua

CoRR, 2018

Improving Stock Movement Prediction with Adversarial Training.

Fuli Feng, Huimin Chen, Xiangnan He, Ji Ding, Maosong Sun, Tat-Seng Chua

CoRR, 2018

Visually-aware Collaborative Food Recommendation.

Xiaoyan Gao, Fuli Feng, Xiangnan He, Heyan Huang, Xinyu Guan, Chong Feng, Zhaoyan Ming, Tat-Seng Chua

CoRR, 2018

Sampler Design for Bayesian Personalized Ranking by Leveraging View Data.

Jingtao Ding, Guanghui Yu, Xiangnan He, Yong Li, Depeng Jin

CoRR, 2018

Learning Recommender Systems from Multi-Behavior Data.

Chen Gao, Xiangnan He, Dahua Gan, Xiangning Chen, Fuli Feng, Yong Li, Tat-Seng Chua, Depeng Jin

CoRR, 2018

A Simple but Hard-to-Beat Baseline for Session-based Recommendations.

Fajie Yuan, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M. Jose, Xiangnan He

CoRR, 2018

Aesthetic-based Clothing Recommendation.

Wenhui Yu, Huidi Zhang, Xiangnan He, Xu Chen, Li Xiong, Zheng Qin

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

TEM: Tree-enhanced Embedding Model for Explainable Recommendation.

Xiang Wang, Xiangnan He, Fuli Feng, Liqiang Nie, Tat-Seng Chua

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Learning on Partial-Order Hypergraphs.

Fuli Feng, Xiangnan He, Yiqun Liu, Liqiang Nie, Tat-Seng Chua

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

An Improved Sampler for Bayesian Personalized Ranking by Leveraging View Data.

Jingtao Ding, Fuli Feng, Xiangnan He, Guanghui Yu, Yong Li, Depeng Jin

Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

f_BGD: Learning Embeddings From Positive Unlabeled Data with BGD.

Fajie Yuan, Xin Xin, Xiangnan He, Guibing Guo, Weinan Zhang, Tat-Seng Chua, Jose M. Joemon

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

A Personal Privacy Preserving Framework: I Let You Know Who Can See What.

Xuemeng Song, Xiang Wang, Liqiang Nie, Xiangnan He, Zhumin Chen, Wei Liu

Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018

Information Discovery in E-commerce: Half-day SIGIR 2018 Tutorial.

Zhaochun Ren, Xiangnan He, Dawei Yin, Maarten de Rijke

Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018

Fast Scalable Supervised Hashing.

Xin Luo, Liqiang Nie, Xiangnan He, Ye Wu, Zhen-Duo Chen, Xin-Shun Xu

Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018

Attentive Moment Retrieval in Videos.

Meng Liu, Xiang Wang, Liqiang Nie, Xiangnan He, Baoquan Chen, Tat-Seng Chua

Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018

Attentive Group Recommendation.

Da Cao, Xiangnan He, Lianhai Miao, Yahui An, Chao Yang, Richang Hong

Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018

Adversarial Personalized Ranking for Recommendation.

Xiangnan He, Zhankui He, Xiaoyu Du, Tat-Seng Chua

Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018

BiNE: Bipartite Network Embedding.

Ming Gao, Leihui Chen, Xiangnan He, Aoying Zhou

Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018

Venue Prediction for Social Images by Exploiting Rich Temporal Patterns in LBSNs.

Jingyuan Chen, Xiangnan He, Xuemeng Song, Hanwang Zhang, Liqiang Nie, Tat-Seng Chua

Proceedings of the MultiMedia Modeling - 24th International Conference, 2018

Knowledge-aware Multimodal Dialogue Systems.

Lizi Liao, Yunshan Ma, Xiangnan He, Richang Hong, Tat-Seng Chua

Proceedings of the 2018 ACM Multimedia Conference on Multimedia Conference, 2018

Interpretable Multimodal Retrieval for Fashion Products.

Lizi Liao, Xiangnan He, Bo Zhao, Chong-Wah Ngo, Tat-Seng Chua

Proceedings of the 2018 ACM Multimedia Conference on Multimedia Conference, 2018

Beyond the Product: Discovering Image Posts for Brands in Social Media.

Francesco Gelli, Tiberio Uricchio, Xiangnan He, Alberto Del Bimbo, Tat-Seng Chua

Proceedings of the 2018 ACM Multimedia Conference on Multimedia Conference, 2018

Recommendation Technologies for Multimedia Content.

Xiangnan He, Hanwang Zhang, Tat-Seng Chua

Proceedings of the 2018 ACM on International Conference on Multimedia Retrieval, 2018

Cross-Domain Depression Detection via Harvesting Social Media.

Tiancheng Shen, Jia Jia, Guangyao Shen, Fuli Feng, Xiangnan He, Huanbo Luan, Jie Tang, Thanassis Tiropanis, Tat-Seng Chua, Wendy Hall

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Discrete Factorization Machines for Fast Feature-based Recommendation.

Han Liu, Xiangnan He, Fuli Feng, Liqiang Nie, Rui Liu, Hanwang Zhang

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Improving Implicit Recommender Systems with View Data.

Jingtao Ding, Guanghui Yu, Xiangnan He, Yuhan Quan, Yong Li, Tat-Seng Chua, Depeng Jin, Jiajie Yu

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

A^3NCF: An Adaptive Aspect Attention Model for Rating Prediction.

Zhiyong Cheng, Ying Ding, Xiangnan He, Lei Zhu, Xuemeng Song, Mohan S. Kankanhalli

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Outer Product-based Neural Collaborative Filtering.

Xiangnan He, Xiaoyu Du, Xiang Wang, Feng Tian, Jinhui Tang, Tat-Seng Chua

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

A Graph-Theoretic Fusion Framework for Unsupervised Entity Resolution.

Dongxiang Zhang, Long Guo, Xiangnan He, Jie Shao, Sai Wu, Heng Tao Shen

Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

Sequicity: Simplifying Task-oriented Dialogue Systems with Single Sequence-to-Sequence Architectures.

Wenqiang Lei, Xisen Jin, Min-Yen Kan, Zhaochun Ren, Xiangnan He, Dawei Yin

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

Batch IS NOT Heavy: Learning Word Representations From All Samples.

Xin Xin, Fajie Yuan, Xiangnan He, Joemon M. Jose

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

Group-Pair Convolutional Neural Networks for Multi-View Based 3D Object Retrieval.

Zan Gao, Deyu Wang, Xiangnan He, Hua Zhang

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Cross-Platform App Recommendation by Jointly Modeling Ratings and Texts.

Da Cao, Xiangnan He, Liqiang Nie, Xiaochi Wei, Xia Hu, Shunxiang Wu, Tat-Seng Chua

ACM Trans. Inf. Syst., 2017

Discrete Multimodal Hashing With Canonical Views for Robust Mobile Landmark Search.

Lei Zhu, Zi Huang, Xiaobai Liu, Xiangnan He, Jiande Sun, Xiaofang Zhou

IEEE Trans. Multim., 2017

BiRank: Towards Ranking on Bipartite Graphs.

Xiangnan He, Ming Gao, Min-Yen Kan, Dingxian Wang

IEEE Trans. Knowl. Data Eng., 2017

A Truthful Incentive Mechanism for Online Recruitment in Mobile Crowd Sensing System.

Xiao Chen, Min Liu, Yaqin Zhou, Zhongcheng Li, Shuang Chen, Xiangnan He

Sensors, 2017

Version-sensitive mobile App recommendation.

Da Cao, Liqiang Nie, Xiangnan He, Xiaochi Wei, Jialie Shen, Shunxiang Wu, Tat-Seng Chua

Inf. Sci., 2017

Discrete Multi-modal Hashing with Canonical Views for Robust Mobile Landmark Search.

Lei Zhu, Zi Huang, Xiaobai Liu, Xiangnan He, Jingkuan Song, Xiaofang Zhou

CoRR, 2017

Neural Collaborative Filtering.

Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, Tat-Seng Chua

Proceedings of the 26th International Conference on World Wide Web, 2017

A Generic Coordinate Descent Framework for Learning from Implicit Feedback.

Immanuel Bayer, Xiangnan He, Bhargav Kanagal, Steffen Rendle

Proceedings of the 26th International Conference on World Wide Web, 2017

Item Silk Road: Recommending Items from Information Domains to Social Users.

Xiang Wang, Xiangnan He, Liqiang Nie, Tat-Seng Chua

Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017

Attentive Collaborative Filtering: Multimedia Recommendation with Item- and Component-Level Attention.

Jingyuan Chen, Hanwang Zhang, Xiangnan He, Liqiang Nie, Wei Liu, Tat-Seng Chua

Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017

Embedding Factorization Models for Jointly Recommending Items and User Generated Lists.

Da Cao, Liqiang Nie, Xiangnan He, Xiaochi Wei, Shunzhi Zhu, Tat-Seng Chua

Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017

Neural Factorization Machines for Sparse Predictive Analytics.

Xiangnan He, Tat-Seng Chua

Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017

Video Question Answering via Gradually Refined Attention over Appearance and Motion.

Dejing Xu, Zhou Zhao, Jun Xiao, Fei Wu, Hanwang Zhang, Xiangnan He, Yueting Zhuang

Proceedings of the 2017 ACM on Multimedia Conference, 2017

Enhancing Micro-video Understanding by Harnessing External Sounds.

Liqiang Nie, Xiang Wang, Jianglong Zhang, Xiangnan He, Hanwang Zhang, Richang Hong, Qi Tian

Proceedings of the 2017 ACM on Multimedia Conference, 2017

Multiview and Multimodal Pervasive Indoor Localization.

Zhenguang Liu, Li Cheng, Anan Liu, Luming Zhang, Xiangnan He, Roger Zimmermann

Proceedings of the 2017 ACM on Multimedia Conference, 2017

How Personality Affects our Likes: Towards a Better Understanding of Actionable Images.

Francesco Gelli, Xiangnan He, Tao Chen, Tat-Seng Chua

Proceedings of the 2017 ACM on Multimedia Conference, 2017

Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks.

Jun Xiao, Hao Ye, Xiangnan He, Hanwang Zhang, Fei Wu, Tat-Seng Chua

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Representativeness-aware Aspect Analysis for Brand Monitoring in Social Media.

Lizi Liao, Xiangnan He, Zhaochun Ren, Liqiang Nie, Huan Xu, Tat-Seng Chua

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

SWIM: A Simple Word Interaction Model for Implicit Discourse Relation Recognition.

Wenqiang Lei, Xuancong Wang, Meichun Liu, Ilija Ilievski, Xiangnan He, Min-Yen Kan

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

SMASC 2017: First International Workshop on Social Media Analytics for Smart Cities.

Manjira Sinha, Xiangnan He, Alessandro Bozzon, Sandya Mannarswamy, Pradeep K. Murukannaiah, Tridib Mukherjee

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

2016

Discrete Collaborative Filtering.

Hanwang Zhang, Fumin Shen, Wei Liu, Xiangnan He, Huanbo Luan, Tat-Seng Chua

Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016

Fast Matrix Factorization for Online Recommendation with Implicit Feedback.

Xiangnan He, Hanwang Zhang, Min-Yen Kan, Tat-Seng Chua

Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016

Shorter-is-Better: Venue Category Estimation from Micro-Video.

Jianglong Zhang, Liqiang Nie, Xiang Wang, Xiangnan He, Xianglin Huang, Tat-Seng Chua

Proceedings of the 2016 ACM Conference on Multimedia Conference, 2016

Context-aware Image Tweet Modelling and Recommendation.

Tao Chen, Xiangnan He, Min-Yen Kan

Proceedings of the 2016 ACM Conference on Multimedia Conference, 2016

2015

Differential spread strategy: An incentive for advertisement dissemination.

Xiao Chen, Min Liu, Yaqin Zhou, Zhongcheng Li, Shuang Chen, Xiangnan He

Proceedings of the 2015 IEEE Symposium on Computers and Communication, 2015

TriRank: Review-aware Explainable Recommendation by Modeling Aspects.

Xiangnan He, Tao Chen, Min-Yen Kan, Xiao Chen

Proceedings of the 24th ACM International Conference on Information and Knowledge Management, 2015

VELDA: Relating an Image Tweet's Text and Images.

Tao Chen, Hany M. SalahEldeen, Xiangnan He, Min-Yen Kan, Dongyuan Lu

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Comment-based multi-view clustering of web 2.0 items.

Xiangnan He, Min-Yen Kan, Peichu Xie, Xiao Chen

Proceedings of the 23rd International World Wide Web Conference, 2014

Predicting the popularity of web 2.0 items based on user comments.

Xiangnan He, Ming Gao, Min-Yen Kan, Yiqun Liu, Kazunari Sugiyama

Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2014

2013

Mining Scientific Terms and their Definitions: A Study of the ACL Anthology.

Yiping Jin, Min-Yen Kan, Jun-Ping Ng, Xiangnan He

Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, 2013

2010

Recording How-Provenance on Probabilistic Databases.

Ming Gao, Xiangnan He, Cheqing Jin, Xiaoling Wang, Aoying Zhou

Proceedings of the Advances in Web Technologies and Applications, 2010