Jointly Modeling Individual Student Behaviors and Social Influence for Prediction Tasks. - Haobing Liu 001; Yanmin Zhu 006; Tianzi Zang; Jiadi Yu; Haibin Cai (CIKM, 2020)

Modeling Local and Global Flow Aggregation for Traffic Flow Forecasting. - Yuan Qu; Yanmin Zhu 006; Tianzi Zang; Yanan Xu; Jiadi Yu (WISE (1), 2020)

Learning from Multiple Graphs of Student and Book Interactions for Campus Book Recommendation. - Qiaomei Zhang; Yanmin Zhu 006; Tianzi Zang; Jiadi Yu (WISE (2), 2020)

Enhancing User Interest Modeling with Knowledge-Enriched Itemsets for Sequential Recommendation. - Chunyang Wang 001; Yanmin Zhu 006; Haobing Liu 001; Wenze Ma; Tianzi Zang; Jiadi Yu (CIKM, 2021)

Modeling Dynamic Social Behaviors with Time-Evolving Graphs for User Behavior Predictions. - Tianzi Zang; Yanmin Zhu 006; Chen Gong; Haobing Liu 001; Bo Li 001 (DASFAA (1), 2021)

Modeling Inter-station Relationships with Attentive Temporal Graph Convolutional Network for Air Quality Prediction. - Chunyang Wang 001; Yanmin Zhu 006; Tianzi Zang; Haobing Liu 001; Jiadi Yu (WSDM, 2021)

Jointly Modeling Spatio-Temporal Dependencies and Daily Flow Correlations for Crowd Flow Prediction. - Tianzi Zang; Yanmin Zhu 006; Yanan Xu; Jiadi Yu (ACM Trans. Knowl. Discov. Data, 2021)

Multi-Level Attention Networks for Multi-Step Citywide Passenger Demands Prediction. - Xian Zhou 003; Yanyan Shen; Linpeng Huang; Tianzi Zang; Yanmin Zhu 006 (IEEE Trans. Knowl. Data Eng., 2021)

Inter- and Intra-Domain Relation-Aware Heterogeneous Graph Convolutional Networks for Cross-Domain Recommendation. - Ke Wang 038; Yanmin Zhu 006; Haobing Liu 001; Tianzi Zang; Chunyang Wang 001; Kuan Liu (DASFAA (2), 2022)

Graph Contrastive Learning with Adaptive Augmentation for Recommendation. - Mengyuan Jing; Yanmin Zhu 006; Tianzi Zang; Jiadi Yu; Feilong Tang 001 (ECML/PKDD (1), 2022)

Deep Meta-learning in Recommendation Systems: A Survey. - Chunyang Wang 001; Yanmin Zhu 006; Haobing Liu 001; Tianzi Zang; Jiadi Yu; Feilong Tang 001 (CoRR, 2022)

MPAN: Multi-parallel attention network for session-based recommendation. - Tianzi Zang; Yanmin Zhu 006; Jing Zhu; Yanan Xu; Haobing Liu 001 (Neurocomputing, 2022)

Jointly Modeling Heterogeneous Student Behaviors and Interactions among Multiple Prediction Tasks. - Haobing Liu 001; Yanmin Zhu 006; Tianzi Zang; Yanan Xu; Jiadi Yu; Feilong Tang 001 (ACM Trans. Knowl. Discov. Data, 2022)

Disentangled Contrastive Learning for Cross-Domain Recommendation. - Ruohan Zhang; Tianzi Zang; Yanmin Zhu 006; Chunyang Wang 001; Ke Wang 038; Jiadi Yu (DASFAA (2), 2023)

Multi-scale Spin Convolutional Neural Network for Typhoon Intensity Prediction. - Longjie Li 006; Yanmin Zhu 006; Han Zhang; Mengyuan Jing; Haoyu Zhang; Zhaobo Wang; Tianzi Zang (ICPADS, 2023)

Rating-Review Graph Contrastive Learning for Review-based Recommendation. - Jiacheng Shi; Yanmin Zhu 006; Ke Wang 038; Mengyuan Jing; Tianzi Zang; Jiadi Yu; Feilong Tang 001 (ICPADS, 2023)

Dual Contrastive Learning for Multi-Behavior Recommendation. - Jiahui Wang; Yanmin Zhu 006; Mengyuan Jing; Tianzi Zang; Qinghua Chen (ICPADS, 2023)

Learning Aspect-Aware High-Order Representations from Ratings and Reviews for Recommendation. - Ke Wang 038; Yanmin Zhu 006; Haobing Liu 001; Tianzi Zang; Chunyang Wang 001 (ACM Trans. Knowl. Discov. Data, 2023)

A Survey on Cross-domain Recommendation: Taxonomies, Methods, and Future Directions. - Tianzi Zang; Yanmin Zhu 006; Haobing Liu 001; Ruohan Zhang; Jiadi Yu (ACM Trans. Inf. Syst., 2023)

Learning Shared Representations for Recommendation with Dynamic Heterogeneous Graph Convolutional Networks. - Mengyuan Jing; Yanmin Zhu 006; Yanan Xu; Haobing Liu 001; Tianzi Zang; Chunyang Wang 001; Jiadi Yu (ACM Trans. Knowl. Discov. Data, 2023)

Enhancing length of stay prediction by learning similarity-aware representations for hospitalized patients. - Tianzi Zang; Yanmin Zhu 006; Xinrui Huang; Xinchen Yang; Qiuxia Chen; Jiadi Yu; Feilong Tang 001 (Artif. Intell. Medicine, 2023)

Multifaceted Relation-aware Meta-learning with Dual Customization for User Cold-start Recommendation. - Chunyang Wang 001; Yanmin Zhu 006; Haobing Liu 001; Tianzi Zang; Ke Wang 038; Jiadi Yu (ACM Trans. Knowl. Discov. Data, 2023)

Review-Enhanced Hierarchical Contrastive Learning for Recommendation. - Ke Wang 038; Yanmin Zhu 006; Tianzi Zang; Chunyang Wang 001; Mengyuan Jing (AAAI, 2024)

Efficient and Secure Contribution Estimation in Vertical Federated Learning. - Juan Li 011; Rui Deng; Tianzi Zang; Mingqi Kong; Kun Zhu 001 (CIKM, 2024)

All Federated or Not: Optimizing Personal Model Performance in Cross-silo Federated Learning. - Juan Li 011; Yanmin Zhu 006; Jie Wu 001; Weifan Wu; Tianzi Zang; Liu Lu (ICPADS, 2024)

Federated Learning with Data-Free Distillation for Heterogeneity-Aware Autonomous Driving. - Junyao Liang; Juan Li 011; Ji Zhang; Tianzi Zang (IJCNN, 2024)

Model Selection Based on DRL: Improving Personal Model Performance in Federated Learning. - Zishang Chen; Juan Li 011; Kun Zhu 001; Changyan Yi; Tianzi Zang (WCNC, 2024)

Contrastive Self-supervised Learning in Recommender Systems: A Survey. - Mengyuan Jing; Yanmin Zhu 006; Tianzi Zang; Ke Wang 038 (ACM Trans. Inf. Syst., 2024)

Multi-aspect Graph Contrastive Learning for Review-enhanced Recommendation. - Ke Wang 038; Yanmin Zhu 006; Tianzi Zang; Chunyang Wang 001; Kuan Liu; Peibo Ma (ACM Trans. Inf. Syst., 2024)

Contrastive Multi-view Interest Learning for Cross-domain Sequential Recommendation. - Tianzi Zang; Yanmin Zhu 006; Ruohan Zhang; Chunyang Wang 001; Ke Wang 038; Jiadi Yu (ACM Trans. Inf. Syst., 2024)

Explicitly modeling relationships between domain-specific and domain-invariant interests for cross-domain recommendation. - Tianzi Zang; Yanmin Zhu 006; Ruohan Zhang; Jing Zhu; Feilong Tang 001 (World Wide Web (WWW), 2024)

Beyond Homophily: Graph Contrastive Learning with Macro-Micro Message Passing. - Yiyuan Chen; Donghai Guan; Weiwei Yuan; Tianzi Zang (AAAI, 2025)

A Multi-Focus-Driven Multi-Branch Network for Robust Multimodal Sentiment Analysis. - Chuanqi Tao; Jiaming Li; Tianzi Zang; Peng Gao (AAAI, 2025)

Reinforcement Learning-Based Dual-Identity Double Auction in Personalized Federated Learning. - Juan Li 011; Zishang Chen; Tianzi Zang; Tong Liu 001; Jie Wu 001; Yanmin Zhu 006 (IEEE Trans. Mob. Comput., 2025)