Yanyan SHEN (沈艳艳)

Associate Professor with Tenure
SEIEE Building #03-528
Data Driven Software Technology Lab
Shanghai Jiao Tong University
Email: shenyy AT sjtu DOT edu DOT cn

• Lifan Zhao, Shuming Kong, Yanyan Shen. DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend Forecasting. In KDD, 2023.
• Qiqi Zhou, Yanyan Shen, Lei Chen. Narrow the Input Mismatch in Deep Graph Neural Network Distillation. In KDD, 2023.
• Zhikai Wang, Yanyan Shen, Zibin Zhang, Kangyi Lin. Feature Staleness Aware Incremental Learning for CTR Prediction. In IJCAI, 2023.
• Yiming Li, Yanyan Shen, et al. Orca: Scalable Temporal Graph Neural Networks Training with Theoretical Guarantees. In SIGMOD, 2023.
• Xin Zhang, Yanyan Shen, Yingxia Shao, Lei Chen. DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with GPU. In SIGMOD, 2023.
• Jia Li, Yanyan Shen, et al. SSIN: Self-Supervised Learning for Rainfall Spatial Interpolation. In SIGMOD, 2023.
• Zhikai Wang, Yanyan Shen. Incremental Learning for Multi-Interest Sequential Recommendation. In ICDE, 2023. Best Paper Award
• Yiming Li, Yanyan Shen, et al. Zebra: When Temporal Graph Neural Networks Meet Temporal Personalized PageRank. In PVLDB, 2023.
• Tong Li, Jiale Deng, Yanyan Shen, et al. Towards Fine-grained Explainability for Heterogeneous Graph Neural Network. In AAAI, 2023.
• Shuming Kong, Yanyan Shen, et al. Resolving Training Biases via Influence-based Data Relabeling. In Proceedings of the 10th International Conference on Learning Representations (ICLR), 2022. (oral, accept rate = 54/3391)
• Shuming Kong, Weiyu Cheng, Yanyan Shen, Linpeng Huang. AutoSrh: An Embedding Dimensionality Search Framework for Tabular Data Prediction. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.
• Yanyan Shen, Lifan Zhao, et al. RESUS: Warm-Up Cold Users via Meta-Learning Residual User Preferences in CTR Prediction. ACM Transactions on Information Systems (TOIS), 2022.
• Yiming Li, Yanyan Shen, et al. Camel: Managing Data for Efficient Stream Learning. In Proceedings of the 2022 International Conference on Management of Data (SIGMOD), 2022.
• Qiyu Liu, Yanyan Shen, et al. LHI: A Learned Hamming Space Index Framework for Efficient Similarity Search. In Proceedings of the 2022 International Conference on Management of Data (SIGMOD), 2022.
• Jingzhi Fang, Yanyan Shen, et al. ETO: Accelerating Optimization of DNN Operators by High-Performance Tensor Program Reuse. In Proceedings of the VLDB Endowment (PVLDB), 2022.
• Jingshu Peng, et al. Sancus: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks. In Proceedings of the VLDB Endowment (PVLDB), 2022.
• Runjin Chen, Tong Li, Yanyan Shen, et al. GCF-RD: A Graph-based Contrastive Framework for Semi-Supervised Learning on Relational Databases. In Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM), 2022.
• Xin Zhang, Yanyan Shen, et al. Feature-Oriented Sampling for Fast and Scalable GNN Learning. In Proceedings of the 2022 IEEE International Conference on Data Mining (ICDM), 2022. (accept rate = 85/870)
• Zhikai Wang, Yanyan Shen. Time-aware Multi-interest Capsule Network for Sequential Recommendation. In Proceedings of the SIAM International Conference on Data Mining (SDM), 2022. (accept rate=83/298)
• Yanyan Shen, Baoyuan Ou, Ranzhen Li. MBN: Towards Multi-behavior Sequence Modeling for Next Basket Recommendation. ACM Transactions on Knowledge Discovery from Data (TKDD), 2022.
• Weiyu Cheng, Yanyan Shen, et al. Dual-Embedding based Deep Latent Factor Models for Recommendation. ACM Transactions on Knowledge Discovery from Data (TKDD), 2021.
• Runjin Chen, Yanyan Shen, et al. GNEM: A Generic One-to-Set Neural Entity Matching Framework. In Proceedings of the Web Conference (TheWebConf), 2021.
• Qiyu Liu, Yanyan Shen, et al. LHist: Towards Learning Multi-dimensional Histogram for Massive Spatial Data. In Proceedings of the 37th IEEE International Conference on Data Engineering (ICDE), 2021.
• Yiming Li, Yanyan Shen, et al. Palette: Towards Multi-source Model Selection and Ensemble for Reuse. In Proceedings of the 37th IEEE International Conference on Data Engineering (ICDE), 2021.
• Jia Li, Shimin Di, Yanyan Shen, et al. FluxEV: A Fast and Effective Unsupervised Framework for Time-Series Anomaly Detection. In Proceedings of the 14th ACM International Conference on Web Search and Data Mining (WSDM), 2021. (accept rate=112/603)
• Xujia Li, Yanyan Shen, et al. Mcore: Multi-Agent Collaborative Learning for Knowledge-Graph-Enhanced Recommendation. In Proceedings of the 2021 IEEE International Conference on Data Mining (ICDM), 2021. (accept rate = 98/990)
• Jingshu Peng, Yanyan Shen, et al. GraphANGEL: Adaptive and Structure-Aware Sampling on Graph Neural Networks. In Proceedings of the 2021 IEEE International Conference on Data Mining (ICDM), 2021. (accept rate = 98/990)
• Liujun Wang, Yanyan Shen. BOUNCE: An Efficient Selective Enumeration Approach for Nested Named Entity Recognition. In Proceedings of the 5th Asia Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data (APWeb-WAIM), 2021. (full, accept rate = 44/172)
• Jingzhi Fang, Yanyan Shen, et al. Optimizing DNN Computation Graph using Graph Substitutions. In Proceedings of the VLDB Endowment (PVLDB), 2020.
• Qiyu Liu, Libin Zheng, Yanyan Shen, et al. Stable Learned Bloom Filters for Data Streams. In Proceedings of the VLDB Endowment (PVLDB), 2020.
• Weiyu Cheng, Yanyan Shen, et al. Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions. In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020. (accept rate=1591/7737)
• Xian Zhou, Yanyan Shen, et al. FreqST: Exploiting Frequency Information in Spatiotemporal Modeling for Traffic Prediction. In Proceedings of the 2020 IEEE International Conference on Data Mining (ICDM), 2020. (accept rate = 19.7%)

• [Fall] Database Principles (undergraduate students)
• [Spring] Computer Architecture (cs undergraduate students)
• [Spring] English for Academic Purposes (cs doctoral students)
• Problem Solving and Programming Practice (cs undergraduate students)
• Programming: Practice and Core Guidelines (2016/2017/2018)
• Programming Language (2016/2017)