You may also see our work on Google Scholar. Please find our open-sourced works on our Lab GitHub.
[1] Joint Modeling in Deep Recommender Systems
Pengyue Jia, Jingtong Gao, Yuhao Wang, Xiaopeng Li, Qidong Liu, Yichao Wang, Bo Chen, Huifeng Guo, Ruiming Tang
WWW’25, Proceedings of the ACM Web Conference 2025
[2] Web-Centric Human Mobility Analytics: Methods, Applications, and Future Directions in the LLM Era
Zijian Zhang, Hao Miao, Yuxuan Liang, Yan Zhao, Xiao Han, Pengyue Jia, Bin Yang, Christian S. Jensen
WWW’25, Proceedings of the ACM Web Conference 2025
[3] AgentIR: 1st Workshop on Agent-based Information Retrieval
Qingpeng Cai, Xiangyu Zhao, Ling Pan, Xin Xin, Jin Huang, Weinan Zhang, Li Zhao, Dawei Yin, Grace Hui Yang
SIGIR’24, Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval
[4] Joint Modeling in Recommendations: Foundations and Frontiers
Xiangyu Zhao, Yichao Wang, Bo Chen, Pengyue Jia, Yuhao Wang, Jingtong Gao, Huifeng Guo, Ruiming Tang
IJCAI’23, Proceedings of the 32nd International Joint Conference on Artificial Intelligence
[5] Trustworthy Recommender Systems: Foundations and Frontiers
Wenqi Fan, Xiangyu Zhao, Lin Wang, Xiao Chen, Jingtong Gao, Qidong Liu, Shijie Wang
IJCAI’23, Proceedings of the 32nd International Joint Conference on Artificial Intelligence
KDD’23, Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
[CITE]
[6] A Comprehensive Survey on Trustworthy Recommender Systems
Wenqi Fan, Xiangyu Zhao, Xiao Chen, Jingran Su, Jingtong Gao, Lin Wang, Qidong Liu, Yiqi Wang, Han Xu, Lei Chen, Qing Li
WWW’23, Companion Proceedings of the Web Conference 2023
[CITE]
[5] AutoML for Deep Recommender Systems: Fundamentals and Advances
Ruiming Tang, Bo Chen, Yejing Wang, Huifeng Guo, Yong Liu, Wenqi Fan, Xiangyu Zhao
WSDM’23, Proceedings of the 16th ACM International Conference on Web Search and Data Mining
[CITE]
[7] Automated Machine Learning for Recommendations: Fundamentals and Advances
Xiangyu Zhao, Wenqi Fan, Bo Chen, Ruiming Tang
WWW’22, Companion Proceedings of the Web Conference 2022
[CITE]
[8] Deep Recommender System: Fundamentals and Advances
Xiangyu Zhao, Wenqi Fan, Dawei Yin, Jiliang Tang
WWW’21, Companion Proceedings of the Web Conference 2021
[CITE]
[9] Deep Learning for Recommendations: Fundamentals and Advances
Wenqi Fan, Xiangyu Zhao, Dawei Yin, Jiliang Tang
IJCAI’21, Proceedings of the 30th International Joint Conference on Artificial Intelligence
[1] TAPO: Task-Referenced Adaptation for Prompt Optimization
Wenxin Luo, Weirui Wang, Xiaopeng Li, Weibo Zhou, Pengyue Jia, Xiangyu Zhao
ICASSP’25, Proceedings of the 50th International Conference on Acoustics, Speech, and Signal Processing
[2] LLM-Powered Efficient User Simulator for Recommender System
Zijian Zhang, Shuchang Liu, Ziru Liu, Rui Zhong, Qingpeng Cai, Xiangyu Zhao, Chunxu Zhang, Qidong Liu, Peng Jiang
AAAI’25, Proceedings of the 39th AAAI Conference on Artificial Intelligence
[3] GARLIC: GPT-Augmented Reinforcement Learning with Intelligent Control for Vehicle Dispatching
Xiao Han, Zijian Zhang, Xiangyu Zhao, Yuanshao Zhu, Guojiang Shen, Xiangjie Kong, Xuetao Wei, Liqiang Nie, Jieping Ye
AAAI’25, Proceedings of the 39th AAAI Conference on Artificial Intelligence
[4] Harnessing Large Language Models for Knowledge Graph Question Answering via Adaptive Multi-Aspect Retrieval-Augmentation
Derong Xu, Xinhang Li, Ziheng Zhang, Zhenxi Lin, Zhihong Zhu, Zhi Zheng, Xian Wu, Xiangyu Zhao, Tong Xu, Enhong Chen
AAAI’25, Proceedings of the 39th AAAI Conference on Artificial Intelligence
[5] POI-Enhancer: An LLM-based Semantic Enhancement Framework for POI Representation Learning
Jiawei Cheng, Jingyuan Wang, Yichuan Zhang, Jiahao Ji, Yuanshao Zhu, Zhibo Zhang, Xiangyu Zhao
AAAI’25, Proceedings of the 39th AAAI Conference on Artificial Intelligence
[6] SIGMA: Selective Gated Mamba for Sequential Recommendation
Ziwei Liu, Qidong Liu, Yejing Wang, Wanyu Wang, Pengyue Jia, Maolin Wang, Zitao Liu, Yi Chang, Xiangyu Zhao
AAAI’25, Proceedings of the 39th AAAI Conference on Artificial Intelligence
[7] LLMEmb: Large Language Model Can Be a Good Embedding Generator for Sequential Recommendation
Qidong Liu, Xian Wu, Wanyu Wang, Yejing Wang, Yuanshao Zhu, Xiangyu Zhao, Feng Tian, Yefeng Zheng
AAAI’25, Proceedings of the 39th AAAI Conference on Artificial Intelligence
[8] LLMTreeRec: A Tree-based Large Language Model Framework for Cold-start Recommendation
Wenlin Zhang, Chuhan Wu, Xiangyang Li, Yuhao Wang, Kuicai Dong, Yichao Wang, Xinyi Dai, Xiangyu Zhao, Huifeng Guo, Ruiming Tang
COLING’25, Proceedings of the 31st International Conference on Computational Linguistics
[9] A Contrastive Pretrain Model with Prompt Tuning for Multi-center Medication Recommendation
Qidong Liu, Zhaopeng Qiu, Xiangyu Zhao, Xian Wu, Zijian Zhang, Tong Xu, Feng Tian
TOIS, Transactions on Information Systems
[10] GLINT-RU: Gated Lightweight Intelligent Recurrent Units for Sequential Recommender Systems
Sheng Zhang, Maolin Wang, Wanyu Wang, Jingtong Gao, Xiangyu Zhao, Yu Yang, Xuetao Wei, Zitao Liu, Tong Xu
KDD’25, Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining
[11] DimCL: Dimension-Aware Augmentation in Contrastive Learning for Recomendation
Chi Zhang, Qilong Han, Qiaoyu Tan, Shengjie Wang, Xiangyu Zhao, Rui Chen
KDD’25, Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining
[12] NoteLLM-2: Multimodal Large Representation Models for Recommendation
Chao Zhang, Haoxin Zhang, Shiwei Wu, Di Wu, Tong Xu, Xiangyu Zhao, Yan Gao, Yao Hu, Enhong Chen
KDD’25, Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining
1 online launched system
[1] LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential Recommendation
Qidong Liu, Xian Wu, Xiangyu Zhao, Yejing Wang, Zijian Zhang, Feng Tian, Yefeng Zheng
NeurIPS’24, Proceedings of the 38th Annual Conference on Neural Information Processing Systems
Spotlight(2%)
[2] Unveiling the Bias Impact on Symmetric Moral Consistency of Large Language Models
Ziyi Zhou, Xinwei Guo, Jiashi Gao, Xiangyu Zhao, Shiyao Zhang, Xin Yao, Xuetao Wei
NeurIPS’24, Proceedings of the 38th Annual Conference on Neural Information Processing Systems
[3] Association of Objects May Engender Stereotypes: Mitigating Association-Engendered Stereotypes in Text-to-Image Generation
Junlei Zhou, Jiashi Gao, Xiangyu Zhao, Xin Yao, Xuetao Wei
NeurIPS’24, Proceedings of the 38th Annual Conference on Neural Information Processing Systems
Spotlight(2%)
[4] G3: An Effective and Adaptive Framework for Worldwide Geolocalization Using Large Multi-Modality Models
Pengyue Jia, Yiding Liu, Xiaopeng Li, Xiangyu Zhao, Yuhao Wang, Yantong Du, Xiao Han, Xuetao Wei, Shuaiqiang Wang, Dawei Yin
NeurIPS’24, Proceedings of the 38th Annual Conference on Neural Information Processing Systems
[5] Does Egalitarian Fairness Lead to Instability? The Fairness Bounds in Stable Federated Learning Under Altruistic Behaviors
Jiashi Gao, Ziwei Wang, Xiangyu Zhao, Xin Yao, Xuetao Wei
NeurIPS’24, Proceedings of the 38th Annual Conference on Neural Information Processing Systems
[6] A Unified Framework for Multi-Domain CTR Prediction via Large Language Models
Zichuan Fu, Xiangyang Li, Chuhan Wu, Yichao Wang, Kuicai Dong, Xiangyu Zhao, Mengchen Zhao, Huifeng Guo, Ruiming Tang
TOIS, Transactions on Information Systems
[CITE]
[7] Mitigating Hallucinations of Large Language Models in Medical Domain via Contrastive Decoding
Derong Xu, Ziheng Zhang, Zhihong Zhu, Zhenxi Lin, Qidong Liu, Xian Wu, Tong Xu, Xiangyu Zhao, Yefeng Zheng, Enhong Chen
EMNLP’24, Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
[CITE]
[8] Large Language Models for Generative Information Extraction: A Survey
Derong Xu, Wei Chen, Wenjun Peng, Chao Zhang, Tong Xu, Xiangyu Zhao, Xian Wu, Yefeng Zheng, Yang Wang, Enhong Chen
FCS, Frontiers of Computer Science
[CITE]
[9] Multi-level Graph Knowledge Contrastive Learning
Haoran Yang, Yuhao Wang, Xiangyu Zhao, Hongxu Chen, Hongzhi Yin, Qing Li, Guandong Xu
TKDE, IEEE Transactions on Knowledge and Data Engineering
[CITE]
[10] GPRec: Bi-level User Modeling for Deep Recommender Systems
Yejing Wang, Dong Xu, Xiangyu Zhao, Zhiren Mao, Peng Xiang, Ling Yan, Yao Hu, Zijian Zhang, Xuetao Wei, Qidong Liu
ICDM’24, Proceedings of the 24th International Conference on Data Mining
[11] Multimodal Recommender Systems: A Survey
Qidong Liu, Jiaxi Hu, Yutian Xiao, Xiangyu Zhao, Jingtong Gao, Wanyu Wang, Qing Li, Jiliang Tang
CSUR, ACM Computing Surveys
[CITE]
[12] DNS-Rec: Data-aware Neural Architecture Search for Recommender Systems
Sheng Zhang, Maolin Wang, Xiangyu Zhao, Ruocheng Guo, Yao Zhao, Chenyi Zhuang, Jinjie Gu, Zijian Zhang, Hongzhi Yin
RecSys’24, Proceedings of the 18th ACM Conference on Recommender Systems
[CITE]
[13] Multi-turn Classroom Dialogue Dataset: Assessing Student Performance from One-on-one Conversations
Jiahao Chen, Zitao Liu, Mingliang Hou, Xiangyu Zhao, Weiqi Luo
CIKM’24 (Resource Paper track), Proceedings of the 33rd ACM International Conference on Information and Knowledge Management
[CITE]
[14] Multi-Granularity Modeling in Recommendation: from the Multi-Scenario Perspective
Yuhao Wang
CIKM’24 (PhD Symposium track), Proceedings of the 33rd ACM International Conference on Information and Knowledge Management
[CITE]
[15] Editing Factual Knowledge and Explanatory Ability of Medical Large Language Models
Derong Xu, Ziheng Zhang, Zhihong Zhu, Zhenxi Lin, Qidong Liu, Xian Wu, Tong Xu, Wanyu Wang, Yuyang Ye, Xiangyu Zhao, Yefeng Zheng,
Enhong Chen
CIKM’24 (Full Research Paper track), Proceedings of the 33rd ACM International Conference on Information and Knowledge Management
[CITE]
[16] Efficient and Robust Regularized Federated Recommendation
Langming Liu, Wanyu Wang, Xiangyu Zhao, Zijian Zhang, Chunxu Zhang, Shanru Lin, Yiqi Wang, Lixin Zou, Zitao Liu, Xuetao Wei, Hongzhi Yin,
Qing Li
CIKM’24 (Full Research Paper track), Proceedings of the 33rd ACM International Conference on Information and Knowledge Management
[CITE]
[17] HierRec: Scenario-Aware Hierarchical Modeling for Multi-scenario Recommendations
Jingtong Gao, Bo Chen, Menghui Zhu, Xiangyu Zhao, Xiaopeng Li, Yuhao Wang, Yichao Wang, Huifeng Guo, Ruiming Tang
CIKM’24 (Full Research Paper track), Proceedings of the 33rd ACM International Conference on Information and Knowledge Management
1 online launched system
[CITE]
[18] LLM4MSR: An Effective Efficient Interpretable LLM-Enhanced Paradigm for Multi-Scenario Recommendation
Yuhao Wang, Yichao Wang, Zichuan Fu, Xiangyang Li, Wanyu Wang, Yuyang Ye, Xiangyu Zhao, Huifeng Guo, Ruiming Tang
CIKM’24 (Full Research Paper track), Proceedings of the 33rd ACM International Conference on Information and Knowledge Management
[CITE]
[19] Scalable Dynamic Embedding Size Search for Streaming Recommendation
Yunke Qu, Liang Qu, Tong Chen, Xiangyu Zhao, Quoc Viet Hung Nguyen, Hongzhi Yin
CIKM’24 (Full Research Paper track), Proceedings of the 33rd ACM International Conference on Information and Knowledge Management
[CITE]
[20] Multi-Behavior Recommendation with Personalized Directed Acyclic Behavior Graphs
Xi Zhu, Fake Lin, Ziwei Zhao, Tong Xu, Xiangyu Zhao, Zikai Yin, Xueying Li, Enhong Chen
TOIS, ACM Transactions on Information Systems
[CITE]
[21] Adapting Job Recommendations to User Preference Drift with Behavioral-Semantic Fusion Learning
Xiao Han, Chen Zhu, Xiao Hu, Chuan Qin, Xiangyu Zhao, Hengshu Zhu
KDD’24 (Research track), Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
[CITE]
[22] ControlTraj: Controllable Trajectory Generation with Topology-Constrained Diffusion Model
Yuanshao Zhu, James Jianqiao Yu, Xiangyu Zhao, Qidong Liu, Yongchao Ye, Wei Chen, Zijian Zhang, Xuetao Wei, Yuxuan Liang
KDD’24 (Research track), Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
[CITE]
[23] ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems
Pengyue Jia, Yejing Wang, Zhaocheng Du, Xiangyu Zhao, Yichao Wang, Bo Chen, Wanyu Wang, Huifeng Guo, Ruiming Tang
KDD’24 (ADS track), Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
[CITE]
[24] Modeling User Retention through Generative Flow Networks
Ziru Liu, Shuchang Liu, Bin Yang, Zhenghai Xue, Qingpeng Cai, Xiangyu Zhao, Zijian Zhang, Lantao Hu, Han Li, Peng Jiang
KDD’24 (ADS track), Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
1 online launched system
[CITE]
[25] Automatic Data Repair: Are We Ready to Deploy?
Wei Ni, Xiaoye Miao, Xiangyu Zhao, Yangyang Wu, Shuwei Liang, Jianwei Yin
VLDB’24, Proceedings of the 50th International Conference on Very Large Databases
[CITE]
[26] Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification
Xixun Lin, Wenxiao Zhang, Fengzhao Shi, Chuan Zhou, Lixin Zou, Xiangyu Zhao, Dawei Yin, Shirui Pan, Yanan Cao
ICML’24, Proceedings of the 41st International Conference on Machine Learning
[CITE]
[27] KDDC: Knowledge-Driven Disentangled Causal Metric Learning for Pre-Travel Out-of-Town Recommendation
Yinghui Liu, Guojiang Shen, Chengyong Cui, Zhenzhen Zhao, Xiao Han, Jiaxin Du, Xiangyu Zhao, Xiangjie Kong
IJCAI’24, Proceedings of the 33rd International Joint Conference on Artificial Intelligence
[CITE]
[28] Enhancing Length Generalization for Attention based Knowledge Tracing Models with Linear Biases
Xueyi Li, Youheng Bai, Teng Guo, Zitao Liu, Yaying Huang, Xiangyu Zhao, Feng Xia, Weiqi Luo, Jian Weng
IJCAI’24, Proceedings of the 33rd International Joint Conference on Artificial Intelligence
[CITE]
[29] Sequential Recommendation for Optimizing Both Immediate Feedback and Long-term Retention
Ziru Liu, Shuchang Liu, Zijian Zhang, Qingpeng Cai, Xiangyu Zhao, Kesen Zhao, Lantao Hu, Peng Jiang, Kun Gai
SIGIR’24, Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[30] When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications
Qidong Liu, Xian Wu, Xiangyu Zhao, Yuanshao Zhu, Derong Xu, Feng Tian, Yefeng Zheng
SIGIR’24, Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[31] M3oE: Multi-Domain Multi-Task Mixture-of Experts Recommendation Framework
Zijian Zhang, Shuchang Liu, Jiaao Yu, Qingpeng Cai, Xiangyu Zhao, Chunxu Zhang, Ziru Liu, Qidong Liu, Hongwei Zhao, Lantao Hu,
Peng Jiang, Kun Gai
SIGIR’24, Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[32] Optimal Transport Enhanced Cross-City Site Recommendation
Xinhang Li, Xiangyu Zhao, Zihao Wang, Yang Duan, Yong Zhang, Chunxiao Xing
SIGIR’24, Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[33] OpenSiteRec: An Open Dataset for Site Recommendation
Xinhang Li, Xiangyu Zhao, Yejing Wang, Yu Liu, Chong Chen, Cheng Long, Yong Zhang, Chunxiao Xing
SIGIR’24 (resource track), Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[34] Modeling Net Ecosystem Exchange of CO2 with Gated Recurrent Unit Neural Networks
Huimin Zou, Jiquan Chen, Xianglan Li, Michael Abraha, Xiangyu Zhao, Jiliang Tang
Agricultural and Forest Meteorology
[CITE]
[35] MILL: Mutual Verification with Large Language Models for Zero-Shot Query Expansion
Pengyue Jia, Yiding Liu, Xiangyu Zhao, Xiaopeng Li, Changying Hao, Shuaiqiang Wang, Dawei Yin
NAACL’24, 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics
[CITE]
[36] Mobile Trajectory Anomaly Detection: Taxonomy, Methodology, Challenges, and Directions
Xiangjie Kong, Juntao Wang, Zehao Hu, Yuwei He, Xiangyu Zhao, Guojiang Shen
IoT, IEEE Internet of Things Journal
[CITE]
[37] Multi-perspective Improvement of Knowledge Graph Completion with Large Language Models
Derong Xu, Ziheng Zhang, Zhenxi Lin, Xian Wu, Zhihong Zhu, Tong Xu, Xiangyu Zhao, Yefeng Zheng, Enhong Chen
COLING’24, The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation
[CITE]
[38] Large Multimodal Model Compression via Iterative Efficient Pruning and Distillation
Maolin Wang, Yao Zhao, Jiajia Liu, Jingdong Chen, Chenyi Zhuang, Jinjie Gu, Ruocheng Guo, Xiangyu Zhao
WWW’24 (industry track), Proceedings of the ACM Web Conference 2024
Oral Presentation, 1 online launched system
[CITE]
[39] When Federated Recommendation Meets Cold-Start Problem: Separating Item Attributes and User Interactions
Chunxu Zhang, Guodong Long, Tianyi Zhou, Zijian Zhang, Peng Yan, Bo Yang
WWW’24, Proceedings of the ACM Web Conference 2024
[CITE]
[40] Tensorized Hypergraph Neural Networks
Maolin Wang, Yaoming Zhen, Yu Pan, Yao Zhao, Chenyi Zhuang, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao
SDM’24, Proceedings of the 24th SIAM International Conference on Data Mining
[CITE]
[41] D3: A Methodological Exploration of Domain Division, Modeling, and Balance in Multi-Domain Recommendations
Pengyue Jia, Yichao Wang, Shanru Lin, Xiaopeng Li, Xiangyu Zhao, Huifeng Guo, Ruiming Tang
AAAI’24, Proceedings of the 38th AAAI Conference on Artificial Intelligence
1 online launched system
[CITE]
[42] SSDRec: Self-Augmented Sequence Denoising for Sequential Recommendation
Chi Zhang, Qilong Han, Rui Chen, Xiangyu Zhao, Peng Tang, Hongtao Song
ICDE’24, Proceedings of the 40th IEEE International Conference on Data Engineering
[CITE]
[43] Diff-MSR: A Diffusion Model Enhanced Paradigm for Cold-Start Multi-Scenario Recommendation
Yuhao Wang, Ziru Liu, Yichao Wang, Xiangyu Zhao, Bo Chen, Huifeng Guo, Ruiming Tang
WSDM’24, Proceedings of the 17th ACM International Conference on Web Search and Data Mining
[CITE]
[44] MultiFS: Automated Multi-Scenario Feature Selection in Deep Recommender Systems
Dugang Liu, Chaohua Yang, Xing Tang, Yejing Wang, Fuyuan Lyu, Weihong Luo, Xiuqiang He, Zhong Ming, Xiangyu Zhao
WSDM’24, Proceedings of the 17th ACM International Conference on Web Search and Data Mining
[CITE]
[45] Dynamically Engineered Multi-modal Feature Learning for Predictions of Office Building Cooling Loads
Yiren Liu, Xiangyu Zhao, S. Joe Qin
Applied Energy
[CITE]
[46] Recommender Systems in the Era of Large Language Models (LLMs)
Zihuai Zhao, Wenqi Fan, Jiatong Li, Yunqing Liu, Xiaowei Mei, Yiqi Wang, Zhen Wen, Fei Wang, Xiangyu Zhao, Jiliang Tang, Qing Li
TKDE, IEEE Transactions on Knowledge and Data Engineering
[CITE]
[47] SMLP4Rec: An Efficient all-MLP Architecture for Sequential Recommendations
Jingtong Gao, Xiangyu Zhao, Muyang Li, Minghao Zhao, Runze Wu, Ruocheng Guo, Yiding Liu, Dawei Yin
TOIS, ACM Transactions on Information Systems
[CITE]
[1] On the Opportunities of Green Computing: A Survey
You Zhou, Xiujing Lin, Xiang Zhang, Maolin Wang, Gangwei Jiang, Huakang Lu, Yupeng Wu, Kai Zhang, Zhe Yang, Kehang Wang, Yongduo Sui, Fengwei Jia, Zuoli Tang, Yao Zhao, Hongxuan Zhang, Tiannuo Yang, Weibo Chen, Yunong Mao, Yi Li, De Bao, Yu Li, Hongrui Liao, Ting Liu, Jingwen Liu, Jinchi Guo, Jin Zhao, Xiangyu Zhao, Ying WEI, Hong Qian, Qi Liu, Xiang Wang, Wai Kin (Victor)Chan, Chenliang Li, Yusen Li, Shiyu Yang, Jining Yan, Chao Mou, Shuai Han, Wuxia Jin, Guannan Zhang, Xiaodong Zeng
arxiv preprint
[CITE]
[2] Embedding in Recommender Systems: A Survey
Xiangyu Zhao, Maolin Wang, Xinjian Zhao, Jiansheng Li, Shucheng Zhou, Dawei Yin, Qing Li, Jiliang Tang, Ruocheng Guo
arxiv preprint
[CITE]
[3] A Comprehensive Survey on Automated Machine learning for Recommendations
Bo Chen, Xiangyu Zhao, Yejing Wang, Wenqi Fan, Huifeng Guo, Ruiming Tang
TORS, ACM Transactions on Recommender Systems
[CITE]
[4] An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations
Haoran Yang, Xiangyu Zhao, Yicong Li, Hongxu Chen, Guandong Xu
NeurIPS’23, Proceedings of the 37th Annual Conference on Neural Information Processing Systems
[CITE]
[5] DiffTraj: Generating GPS Trajectory with Diffusion Probabilistic Model
Yuanshao Zhu, Yongchao Ye, Shiyao Zhang, Xiangyu Zhao, James J.Q. Yu
NeurIPS’23, Proceedings of the 37th Annual Conference on Neural Information Processing Systems
[CITE]
[6] SynMob: Creating High-Fidelity Synthetic GPS Trajectory Dataset for Urban Mobility Analysis
Yuanshao Zhu, Yongchao Ye, Ying Wu, Xiangyu Zhao, James J.Q. Yu
NeurIPS’23 (Datasets and Benchmarks track), Proceedings of the 37th Annual Conference on Neural Information Processing Systems
[CITE]
[7] KuaiSim: A Comprehensive Simulator for Recommender Systems
Kesen Zhao, Shuchang Liu, Qingpeng Cai, Xiangyu Zhao, Ziru Liu, Dong Zheng, Peng Jiang, Kun Gai
NeurIPS’23 (Datasets and Benchmarks track), Proceedings of the 37th Annual Conference on Neural Information Processing Systems
[CITE]
[8] XES3G5M: A Knowledge Tracing Benchmark Dataset with Auxiliary Information
Zitao Liu, Qiongqiong Liu, Teng Guo, Jiahao Chen, Shuyan Huang, Xiangyu Zhao, Jiliang Tang, Weiqi Luo, Jian Weng
NeurIPS’23 (Datasets and Benchmarks track), Proceedings of the 37th Annual Conference on Neural Information Processing Systems
[CITE]
[9] Federated Knowledge Graph Completion via Latent Embedding Sharing and Tensor Factorization
Maolin Wang, Dun Zeng, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao
ICDM’23, Proceedings of the 23rd International Conference on Data Mining
[CITE]
[10] Task Assignment with Efficient Federated Preference Learning in Spatial Crowdsourcing
Hao Miao, Xiaolong Zhong, Jiaxin Liu, Yan Zhao, Xiangyu Zhao, Weizhu Qian, Kai Zheng, Christian S. Jensen
TKDE, IEEE Transactions on Knowledge and Data Engineering
[CITE]
[11] Mitigating Performance Sacrifice in DP-satisfied Federated Settings through Graph Contrastive Learning
Haoran Yang, Xiangyu Zhao, Muyang Li, Hongxu Chen, Guandong Xu
INS, Information Sciences
[CITE]
[12] Diffusion Augmentation for Sequential Recommendation
Qidong Liu, Fan Yan, Xiangyu Zhao, Zhaocheng Du, Huifeng Guo, Ruiming Tang, Feng Tian
CIKM’23, Proceedings of the 32nd ACM International Conference on Information & Knowledge Management
[CITE]
[13] Rethinking Sensors Modeling: Hierarchical Information Enhanced Traffic Forecasting
Qian Ma, Zijian Zhang, Xiangyu Zhao, Haoliang Li, Hongwei Zhao, Yiqi Wang, Zitao Liu, Wanyu Wang
CIKM’23, Proceedings of the 32nd ACM International Conference on Information & Knowledge Management
[CITE]
[14] PromptST: Prompt-Enhanced Spatio-Temporal Multi-Attribute Prediction
Zijian Zhang, Xiangyu Zhao, Qidong Liu, Chunxu Zhang, Qian Ma, Wanyu Wang, Hongwei Zhao, Yiqi Wang, Zitao Liu
CIKM’23, Proceedings of the 32nd ACM International Conference on Information & Knowledge Management
[CITE]
[15] MLPST: MLP is All You Need for Spatio-Temporal Prediction
Zijian Zhang, Ze Huang, Zhiwei Hu, Xiangyu Zhao, Wanyu Wang, Zitao Liu, Junbo Zhang, S. Joe Qin, Hongwei Zhao
CIKM’23, Proceedings of the 32nd ACM International Conference on Information & Knowledge Management
[CITE]
[16] REST: Drug-Drug Interaction Prediction via Reinforced Student-Teacher Curriculum Learning
Xinhang Li, Zhaopeng Qiu, Xiangyu Zhao, Yong Zhang, Chunxiao Xing, Xian Wu
CIKM’23, Proceedings of the 32nd ACM International Conference on Information & Knowledge Management
[CITE]
[17] Towards Automatic ICD Coding via Knowledge Enhanced Multi-Task Learning
Xinhang Li, Xiangyu Zhao, Yong Zhang, Chunxiao Xing
CIKM’23, Proceedings of the 32nd ACM International Conference on Information & Knowledge Management
[CITE]
[18] HAMUR: Hyper Adapter for Multi-Domain Recommendation
Xiaopeng Li, Fan Yan, Xiangyu Zhao, Yichao Wang, Huifeng Guo, Bo Chen, Ruiming Tang
CIKM’23, Proceedings of the 32nd ACM International Conference on Information & Knowledge Management
[CITE]
[19] Counterfactual Adversarial Learning for Recommender Systems
Jialin Liu, Zijian Zhang, Xiangyu Zhao, Jun Li
CIKM’23 (short paper), Proceedings of the 32nd ACM International Conference on Information & Knowledge Management
[CITE]
[20] Assessing Student Performance with Multi-granularity Attention from Online Classroom Dialogue
Jiahao Chen, Zitao Liu, Shuyan Huang, Yaying Huang, Xiangyu Zhao, Boyu Gao, Weiqi Lu
CIKM’23 (short paper), Proceedings of the 32nd ACM International Conference on Information & Knowledge Management
[CITE]
[21] AutoAssign+: Automatic Shared Embedding Assignment in Streaming Recommendation
Ziru Liu, Kecheng Chen, Fengyi Song, Bo Chen, Xiangyu Zhao, Huifeng Guo, Ruiming Tang
KAIS, Knowledge and Information Systems
[CITE]
[22] STRec: Sparse Transformer for Sequential Recommendations
Chengxi Li, Xiangyu Zhao, Yejing Wang, Qidong Liu, Wanyu Wang, Yiqi Wang, Lixin Zou, Wenqi Fan, Qing Li
RecSys’23, Proceedings of the 17th ACM Conference on Recommender Systems
[CITE]
[23] Mitigating Action Hysteresis in Traffic Signal Control with Traffic Predictive Reinforcement Learning
Xiao Han, Xiangyu Zhao, Liang Zhang, Wanyu Wang
KDD’23, Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
[CITE]
[24] Doctor Specific Tag Recommendation for Online Medical Record Management
Yejing Wang, Shen Ge, Xiangyu Zhao, Xian Wu, Tong Xu, Chen Ma, Zhi Zheng
KDD’23, Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
[CITE]
[25] Adversarial Attacks for Black-box Recommender Systems via Copying Transferable Cross-domain User Profiles
Wenqi Fan, Xiangyu Zhao, Qing Li, Tyler Derr, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang
TKDE, IEEE Transactions on Knowledge and Data Engineering
[CITE]
[26] LinRec: Linear Attention Mechanism for Long-term Sequential Recommender Systems
Langming Liu, Liu Cai, Chi Zhang, Xiangyu Zhao, Jingtong Gao, Wanyu Wang, Yifu Lv, Wenqi Fan, Yiqi Wang, Ming He, Zitao Liu, Qing Li
SIGIR’23, Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[27] PLATE: A Prompt-enhanced Paradigm for Multi-Scenario Recommendations
Yuhao Wang, Xiangyu Zhao, Bo Chen, Qidong Liu, Huifeng Guo, Huanshuo Liu, Yichao Wang, Rui Zhang, Ruiming Tang
SIGIR’23, Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[28] AutoTransfer: Instance Transfer for Cross-Domain Recommendations
Jingtong Gao, Xiangyu Zhao, Bo Chen, Fan Yan, Huifeng Guo, Ruiming Tang
SIGIR’23, Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[29] Single-shot Feature Selection for Multi-task Recommendations
Yejing Wang, Zhaocheng Du, Xiangyu Zhao, Bo Chen, Huifeng Guo, Ruiming Tang, Zhenhua Dong
SIGIR’23, Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[30] Continuous Input Embedding Size Search For Recommender Systems
Yunke Qu, Tong Chen, Xiangyu Zhao, Lizhen Cui, Kai Zheng, Hongzhi Yin
SIGIR’23, Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[31] AutoDPQ: Automated Differentiable Product Quantization Embedding Compression Framework
Xin Gan, Yuhao Wang, Xiangyu Zhao, Wanyu Wang, Yiqi Wang, Zitao Liu
SIGIR’23 (short paper), Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[32] Towards Robust Knowledge Tracing Models via k-Sparse Attention
Shuyan Huang, Zitao Liu, Xiangyu Zhao, Weiqi Luo, Jian Weng
SIGIR’23 (short paper), Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[33] SC-Ques: A Sentence Completion Question Dataset for English as a Second Language Learners
Qiongqiong Liu, Yaying Huang, Zitao Liu, Shuyan Huang, Jiahao Chen, Xiangyu Zhao, Guimin Lin, Yuyu Zhou, Weiqi Luo
ITS’23, Proceedings of the 19th International Conference on Intelligent Tutoring Systems
[CITE]
[34] Multi-Task Recommendations with Reinforcement Learning
Ziru Liu, Jiejie Tian, Qingpeng Cai, Xiangyu Zhao, Jingtong Gao, Shuchang Liu, Dayou Chen, Tonghao He, Dong Zheng, Peng Jiang, Kun Gai
WWW’23, Proceedings of the ACM Web Conference 2023
[CITE]
[35] AutoDenoise: Automatic Data Instance Denoising for Recommendations
Weilin Lin, Xiangyu Zhao, Yejing Wang, Yuanshao Zhu, Wanyu Wang
WWW’23, Proceedings of the ACM Web Conference 2023
[CITE]
[36] AutoMLP: Automated MLP for Sequential Recommendations
Muyang Li, Zijian Zhang, Xiangyu Zhao, Wanyu Wang, Minghao Zhao, Runze Wu, Ruocheng Guo
WWW’23, Proceedings of the ACM Web Conference 2023
[CITE]
[37] Exploration and Regularization of the Latent Action Space in Recommendation
Shuchang Liu, Qingpeng Cai, Bowen Sun, Yuhao Wang, Ji Jiang, Dong Zheng, Peng Jiang, Kun Gai, Xiangyu Zhao, Yongfeng Zhang
WWW’23, Proceedings of the ACM Web Conference 2023
[CITE]
[38] User Retention-oriented Recommendation with Decision Transformer
Kesen Zhao, Lixin Zou, Xiangyu Zhao, Maolin Wang, Dawei Yin
WWW’23, Proceedings of the ACM Web Conference 2023
[CITE]
[39] Denoising and Prompt-Tuning for Multi-Behavior Recommendation
Chi Zhang, Rui Chen, Xiangyu Zhao, Qilong Han, Li Li
WWW’23, Proceedings of the ACM Web Conference 2023
[CITE]
[40] IMF: Interactive Multimodal Fusion Model for Link Prediction
Xinhang Li, Xiangyu Zhao, Jiaxing Xu, Yong Zhang, Chunxiao Xing
WWW’23, Proceedings of the ACM Web Conference 2023
[CITE]
[41] Generating Counterfactual Hard Negative Samples for Graph Contrastive Learning
Haoran Yang, Hongxu Chen, Sixiao Zhang, Xiangguo Sun, Qian Li, Xiangyu Zhao, Guandong Xu
WWW’23, Proceedings of the ACM Web Conference 2023
[CITE]
[42] MMMLP: Multi-modal Multilayer Perceptron for Sequence Recommendations
Jiahao Liang, Xiangyu Zhao, Muyang Li, Zijian Zhang, Wanyu Wang, Haochen Liu, Zitao Liu
WWW’23, Proceedings of the ACM Web Conference 2023
[CITE]
[43] AutoSTL: Automated Spatio-Temporal Multi-Task Learning
Zijian Zhang, Xiangyu Zhao, Hao Miao, Chunxu Zhang, Hongwei Zhao, Junbo Zhang
AAAI’23, Proceedings of the 37th AAAI Conference on Artificial Intelligence
[CITE]
[44] AutoGen: An Automated Dynamic Model Generation Framework for Recommender System
Chenxu Zhu, Bo Chen, Huifeng Guo, Hang Xu, Xiangyang Li, Xiangyu Zhao, Weinan Zhang, Yong Yu, Ruiming Tang
WSDM’23, Proceedings of the 16th ACM International Conference on Web Search and Data Mining
[CITE]
[1] AutoAssign: Automatic Shared Embedding Assignment in Streaming Recommendation
Fengyi Song, Bo Chen, Xiangyu Zhao, Huifeng Guo, Ruiming Tang
ICDM’22, Proceedings of the 22nd International Conference on Data Mining
Best-ranked Papers
[CITE]
[2] Gromov-Wasserstein Guided Representation Learning for Cross-Domain Recommendation
Xinhang Li, Zhaopeng Qiu, Xiangyu Zhao, Zihao Wang, Yong Zhang, Chunxiao Xing, Xian Wu
CIKM’22, Proceedings of the 31st ACM International Conference on Information & Knowledge Management
[CITE]
[3] Hierarchical Item Inconsistency Signal Learning for Sequence Denoising in Sequential Recommendation
Chi Zhang, Yantong Du, Xiangyu Zhao, Qilong Han, Rui Chen, Li Li
CIKM’22, Proceedings of the 31st ACM International Conference on Information & Knowledge Management
[CITE]
[4] PROPN: Personalized Probabilistic Strategic Parameter Optimization in Recommendations
Pengfei He, Haochen Liu, Xiangyu Zhao, Hui Liu, Jiliang Tang
CIKM’22, Proceedings of the 31st ACM International Conference on Information & Knowledge Management
[CITE]
[5] MAE4Rec: Storage-saving Transformer for Sequential Recommendations
Kesen Zhao, Xiangyu Zhao, Zijian Zhang, Muyang Li
CIKM’22, Proceedings of the 31st ACM International Conference on Information & Knowledge Management
[CITE]
[6] AdaFS: Adaptive Feature Selection in Deep Recommender System
Weilin Lin, Xiangyu Zhao, Yejing Wang, Tong Xu, Xian Wu
KDD’22, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
[CITE]
[7] Knowledge-enhanced Black-box Attacks for Recommendations
Jingfan Chen, Wenqi Fan, Guanghui Zhu, Xiangyu Zhao, Chunfeng Yuan, Qing Li, Yihua Huang
KDD’22, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
[CITE]
[8] DDR: Dialogue Based Doctor Recommendation for Online Medical Service
Zhi Zheng, Zhaopeng Qiu, Hui Xiong, Xian Wu, Tong Xu, Enhong Chen, Xiangyu Zhao
KDD’22, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
[CITE]
[9] DRL4IR: 3rd Workshop on Deep Reinforcement Learning for Information Retrieval
Xiangyu Zhao, Xin Xin, Weinan Zhang, Li Zhao, Dawei Yin, Grace Hui Yang
SIGIR’22, Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[10] CBR: Context Bias aware Recommendation for Debiasing User Modeling and Click Prediction
Zhi Zheng, Zhaopeng Qiu, Tong Xu, Xian Wu, Xiangyu Zhao, Enhong Chen, Hui Xiong
WWW’22, Proceedings of the ACM Web Conference 2022
[CITE]
[11] AutoField: Automating Feature Selection in Deep Recommender Systems
Yejing Wang, Xiangyu Zhao, Tong Xu, Xian Wu
WWW’22, Proceedings of the ACM Web Conference 2022
[CITE]
[12] Rating Distribution Calibration for Selection Bias Mitigation in Recommendations
Haochen Liu, Da Tang, Ji Yang, Xiangyu Zhao, Hui Liu, Jiliang Tang, Youlong Cheng
WWW’22, Proceedings of the ACM Web Conference 2022
[CITE]
[13] MLP4Rec: A Pure MLP Architecture for Sequential Recommendations
Muyang Li, Xiangyu Zhao, Chuan Lyu, Minghao Zhao, Runze Wu, Ruocheng Guo
IJCAI’22, Proceedings of the 31st International Joint Conference on Artificial Intelligence
LONG Oral Presentation (3.75%)
[CITE]
[14] Automated self-supervised learning for graphs
Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang
ICLR’22, Proceedings of the 10th International Conference on Learning Representations
[CITE]
[15] Interaction-aware Drug Package Recommendation via Policy Gradient
Zhi Zheng, Chao Wang, Tong Xu, Dazhong Shen, Penggang Qin, Xiangyu Zhao, Baoxing Huai, Xian Wu, Enhong Chen
TOIS, ACM Transactions on Information Systems
[CITE]
[16] Graph Trend Filtering Networks for Recommendation
Wenqi Fan, Xiaorui Liu, Wei Jin, Xiangyu Zhao, Jiliang Tang, Qing Li
SIGIR’22, Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[17] Multi-Type Urban Crime Prediction
Xiangyu Zhao, Wenqi Fan, Hui Liu, Jiliang Tang
AAAI’22, Proceedings of the AAAI Conference on Artificial Intelligence
[CITE]
[18] DRL4IR: 2nd Workshop on Deep Reinforcement Learning for Information Retrieval
Weinan Zhang, Xiangyu Zhao, Li Zhao, Dawei Yin, Grace Hui Yang
SIGIR’22, Companion Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[1] Data-Efficient Reinforcement Learning for Malaria Control
Lixin Zou, Long Xia, Linfang Hou, Xiangyu Zhao, Dawei Yin
arXiv preprint arXiv:2105.01620
[CITE]
[2] AutoDim: Field-aware Embedding Dimension Search in Recommender Systems
Xiangyu Zhao, Haochen Liu, Hui Liu, Jiliang Tang, Weiwei Guo, Jun Shi, Sida Wang, Huiji Gao, Bo Long
WWW’21, Proceedings of the Web Conference 2021
1 online launched system
[CITE]
[3] UserSim: User Simulation via Supervised Generative Adversarial Network
Xiangyu Zhao, Long Xia, Lixin Zou, Hui Liu, Dawei Yin, Jiliang Tang
WWW’21, Proceedings of the Web Conference 2021
[CITE]
[4] Attacking Black-box Recommendations via Copying Cross-domain User Profiles
Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang, Qing Li
ICDE’21, 2021 IEEE 37th International Conference on Data Engineering
[CITE]
[5] Towards Long-term Fairness in Recommendation
Yingqiang Ge, Shuchang Liu, Ruoyuan Gao, Yikun Xian, Yunqi Li, Xiangyu Zhao, Changhua Pei, Fei Sun, Junfeng Ge, Wenwu Ou, Yongfeng Zhang
WSDM’21, Proceedings of the 14th ACM International Conference on Web Search and Data Mining
Top-4 Most Cited Paper 4 / 155 Accepted Papers
[CITE]
[6] Adaptive and Automated Deep Recommender Systems
Xiangyu Zhao
PhD Thesis, Michigan State University (extended abstract at ACM SIGWEB Newsletter, 2022)
2021 Joint AAAI/ACM SIGAl Doctoral Dissertation Award Nomination
[CITE]
[7] Self-supervised Learning for Alleviating Selection Bias in Recommendation Systems
Haochen Liu, Da Tang, Ji Yang, Xiangyu Zhao, Jiliang Tang, Youlong Cheng
IRS’21, In International Workshop on Industrial Recommendation Systems (IRS) at SIGKDD 2021.
[CITE]
[8] AutoLoss: Automated Loss Function Search in Recommendations
Xiangyu Zhao, Haochen Liu, Wenqi Fan, Hui Liu, Jiliang Tang, Chong Wang
KDD’21, Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data
[CITE]
[9] DEAR: Deep Reinforcement Learning for Online Advertising Impression in Recommender Systems
Xiangyu Zhao, Changsheng Gu, Haoshenglun Zhang, Xiwang Yang, Xiaobing Liu, Hui Liu, Jiliang Tang
AAAI’21, Proceedings of the AAAI Conference on Artificial Intelligence
[CITE]
[10] AutoEmb: Automated embedding dimensionality search in streaming recommendations
Xiangyu Zhao, Chong Wang, Ming Chen, Xudong Zheng, Xiaobing Liu, Jiliang Tang
ICDM’21, Proceedings of the 21st International Conference on Data Mining
Best-ranked Papers, Top-10 Most Cited Paper 10 / 208 Accepted Papers
[CITE]
[1] Whole-Chain Recommendations
Xiangyu Zhao, Long Xia, Lixin Zou, Hui Liu, Dawei Yin, Jiliang Tang
CIKM’20, Proceedings of the 29th ACM International Conference on Information & Knowledge Management
[CITE]
[2] Jointly learning to recommend and advertise
Xiangyu Zhao, Xudong Zheng, Xiwang Yang, Xiaobing Liu, Jiliang Tang
KDD’20, Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
[CITE]
[3] Deep reinforcement learning for information retrieval: Fundamentals and advances
Weinan Zhang, Xiangyu Zhao, Li Zhao, Dawei Yin, Grace Hui Yang, Alex Beutel
SIGIR’20, Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[4] Automated embedding size search in deep recommender systems
Haochen Liu, Xiangyu Zhao, Chong Wang, Xiaobing Liu, Jiliang Tang
SIGIR’20, Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[5] Neural interactive collaborative filtering
Lixin Zou, Long Xia, Yulong Gu, Xiangyu Zhao, Weidong Liu, Jimmy Xiangji Huang, Dawei Yin
SIGIR’20, Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval
[CITE]
[1] Deep reinforcement learning for search, recommendation, and online advertising: a survey
Xiangyu Zhao, Long Xia, Jiliang Tang, Dawei Yin
ACM SIGWEB Newsletter
Top-2 Most Cited Paper 2 / 551 in History
[CITE]
[2] Deep reinforcement learning for page-wise recommendations
Xiangyu Zhao, Long Xia, Liang Zhang, Zhuoye Ding, Dawei Yin, Jiliang Tang
RecSys’18, Proceedings of the 12th ACM Conference on Recommender Systems
Top-1 Most Cited Paper 1 / 117 Accepted Papers
[CITE]
[3] Recommendations with negative feedback via pairwise deep reinforcement learning
Xiangyu Zhao, Liang Zhang, Zhuoye Ding, Long Xia, Jiliang Tang, Dawei Yin
KDD’18, Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
Top-20 Most Cited Paper 19 / 294 Accepted Papers
[CITE]
[4] Crime in urban areas: A data mining perspective
Xiangyu Zhao, Jiliang Tang
ACM SIGKDD Explorations Newsletter
[CITE]
[5] Deep reinforcement learning for list-wise recommendations
Xiangyu Zhao, Liang Zhang, Long Xia, Zhuoye Ding, Dawei Yin, Jiliang Tang
RL4KD’19, 1st Workshop on Deep Reinforcement Learning for Knowledge Discovery
[CITE]
[6] Exploring transfer learning for crime prediction
Xiangyu Zhao, Jiliang Tang
ICDMW’17, 2017 IEEE International Conference on Data Mining Workshops
[CITE]
[7] Incorporating spatio-temporal smoothness for air quality inference
Xiangyu Zhao, Tong Xu, Yanjie Fu, Enhong Chen, Hao Guo
ICDM’17, 2017 IEEE International Conference on Data Mining
[CITE]
[8] Modeling temporal-spatial correlations for crime prediction
Xiangyu Zhao, Jiliang Tang
CIKM’17, Proceedings of the 2017 ACM on Conference on Information and Knowledge Management
Top-20 Most Cited Paper 20 / 350 Accepted Papers
[CITE]
[9] Cosolorec: Joint factor model with content, social, location for heterogeneous point-of-interest recommendation
Hao Guo, Xin Li, Ming He, Xiangyu Zhao, Guiquan Liu, Guandong Xu
KSEM’16, International Conference on Knowledge Science, Engineering and Management
[CITE]
[10] Taxi driving behavior analysis in latent vehicle-to-vehicle networks: A social influence perspective
Tong Xu, Hengshu Zhu, Xiangyu Zhao, Qi Liu, Hao Zhong, Enhong Chen, Hui Xiong
KDD’16, Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
[CITE]
[11] Exploring the choice under conflict for social event participation
Xiangyu Zhao, Tong Xu, Qi Liu, Hao Guo
DASFAA’16, International conference on database systems for advanced applications
[CITE]
[12] Identifying effective multiple spreaders by coloring complex networks
Xiangyu Zhao, Bin Huang, Ming Tang, Haifeng Zhang, Duanbing Chen
EPL, Europhysics Letters
[CITE]
[13] Coloring the complex networks and its application for immunization strategy
Bin Huang, Xianyu Zhao, Kai Qi, Ming Tang
Acta Physica Sinica
[CITE]