Pei, Jian

Mining frequent patterns without candidate generation

Han, J., Pei, J., & Yin, Y. (2000) · ACM SIGMOD Record

Data Mining Algorithms and ApplicationsAdvanced Database Systems and Queries

Cited by 6,402

A Survey on Network Embedding

Cui, P., Wang, X., Pei, J., & Zhu, W. (2019) · IEEE Transactions on Knowledge and Data Engineering

Advanced Graph Neural NetworksComplex Network Analysis Techniques

Cited by 1,274

Constrained frequent pattern mining: a pattern-growth view

Pei, J., & Han, J. (2002) · ACM SIGKDD Explorations Newsletter

Data Mining Algorithms and ApplicationsData Mining and Machine Learning Applications

Cited by 133

Exact and Consistent Interpretation for Piecewise Linear Neural Networks: A Closed Form Solution

Chu, L., Hu, X., Hu, J., Wang, L., & Pei, J. (2018) · Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Explainable Artificial Intelligence (XAI)Neural Networks and Applications

Cited by 87

Discovering outlying aspects in large datasets

Vinh, N. X., Chan, J., Romano, S., Bailey, J., Leckie, C., Ramamohanarao, K., & Pei, J. (2016) · Data Mining and Knowledge Discovery

Anomaly Detection Techniques and ApplicationsData Management and Algorithms

Cited by 83

Mining outlying aspects on numeric data

Duan, L., Tang, G., Pei, J., Bailey, J., Campbell, A., & Tang, C. (2015) · Data Mining and Knowledge Discovery

Anomaly Detection Techniques and ApplicationsData Management and Algorithms

Cited by 70

Artificial Intelligence: Third CAAI International Conference, CICAI 2023, Fuzhou, China, July 22–23, 2023, Revised Selected Papers, Part II

Fang, L., Pei, J., Zhai, G., & Wang, R. (2024) · Lecture Notes in Computer Science

Artificial Intelligence ApplicationsAdvanced Neural Network Applications

Cited by 25

Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation

Zhuang, S., Ren, H., Shou, L., Pei, J., Gong, M., Zuccon, G., & Jiang, D. (2022) · arXiv

Information Retrieval and Search BehaviorTopic Modeling

Cited by 22

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

Liu, B., Li, X., Zhang, J., Wang, J., He, T., Hong, S., Liu, H., Zhang, S., Song, K., Zhu, K., et al. (2025) · arXiv

Psychiatry, Mental Health, NeuroscienceArtificial Intelligence Applications

Cited by 16