| 2025 | ICASSP | Frequency-enhanced Comprehensive Dependency Attention for Time Series Anomaly Detection. | Haonan Chen, Hongzuo Xu, Songlei Jian, Ruyi Zhang, Xingming Li, Zibo Yi |
| 2025 | ICASSP | Deep Time Series Anomaly Detection with Local Temporal Pattern Learning. | Yizhou Li, Yijie Wang, Hongzuo Xu, Xiaohui Zhou |
| 2024 | ICASSP | Boundary-Driven Active Learning for Anomaly Detection in Time Series Data Streams. | Xiaohui Zhou, Yijie Wang, Hongzuo Xu, Mingyu Liu |
| 2024 | ICDE | Hierarchical Adaptive Pooling by Capturing High-order Dependency for Graph Representation Learning (Extended Abstract). | Ning Liu, Songlei Jian, Dongsheng Li, Yiming Zhang, Zhiquan Lai, Hongzuo Xu |
| 2023 | ICASSP | Smoothing Point Adjustment-Based Evaluation of Time Series Anomaly Detection. | Mingyu Liu, Yijie Wang, Hongzuo Xu, Xiaohui Zhou, Bin Li, Yongjun Wang |
| 2023 | ICML | Fascinating Supervisory Signals and Where to Find Them: Deep Anomaly Detection with Scale Learning. | Hongzuo Xu, Yijie Wang, Juhui Wei, Songlei Jian, Yizhou Li, Ning Liu |
| 2023 | ICPADS | Multi-Scale Sampling Based MLP Networks for Anomaly Detection in Multivariate Time Series. | Haojie Li, Hongzuo Xu, Wei Peng, Chiran Shen, Xianwen Qiu |
| 2023 | SMC | Local-Adaptive Transformer for Multivariate Time Series Anomaly Detection and Diagnosis. | Xiaohui Zhou, Yijie Wang, Hongzuo Xu, Mingyu Liu, Ruyi Zhang |
| 2022 | CIKM | Unsupervised Hierarchical Graph Pooling via Substructure-Sensitive Mutual Information Maximization. | Ning Liu, Songlei Jian, Dongsheng Li, Hongzuo Xu |
| 2022 | ICPADS | DPSS: Dynamic Parameter Selection for Outlier Detection on Data Streams. | Ruyi Zhang, Yijie Wang, Haifang Zhou, Bin Li, Hongzuo Xu |
| 2022 | SMC | Factorization Machine-based Unsupervised Model Selection Method | Ruyi Zhang, Yijie Wang, Hongzuo Xu, Haifang Zhou |
| 2021 | ICONIP | OADA: An Online Data Augmentation Method for Raw Histopathology Images. | Zhiyue Wu, Yijie Wang, Haibo Mi, Hongzuo Xu, Wei Zhang, Lanlan Feng |
| 2021 | ICPADS | Effective Anomaly Detection Based on Reinforcement Learning in Network Traffic Data. | Zhongyang Wang, Yijie Wang, Hongzuo Xu, Yongjun Wang |
| 2021 | IJCNN | Integrating Argument-Level Attention with Multi-Level Scores to Predict What Happen Next. | Zhenyu Huang, Yongjun Wang, Hongzuo Xu, Songlei Jian |
| 2021 | WWW | Beyond Outlier Detection: Outlier Interpretation by Attention-Guided Triplet Deviation Network. | Hongzuo Xu, Yijie Wang, Songlei Jian, Zhenyu Huang, Yongjun Wang, Ning Liu, Fei Li |
| 2020 | ICA3PP | Tree2tree Structural Language Modeling for Compiler Fuzzing. | Haoran Xu, Shuhui Fan, Yongjun Wang, Zhijian Huang, Hongzuo Xu, Peidai Xie |
| 2019 | AAAI | Embedding-Based Complex Feature Value Coupling Learning for Detecting Outliers in Non-IID Categorical Data. | Hongzuo Xu, Yongjun Wang, Zhiyue Wu, Yijie Wang |
| 2019 | ICDM | MIX: A Joint Learning Framework for Detecting Both Clustered and Scattered Outliers in Mixed-Type Data. | Hongzuo Xu, Yijie Wang, Yongjun Wang, Zhiyue Wu |
| 2018 | CIKM | Exploring a High-quality Outlying Feature Value Set for Noise-Resilient Outlier Detection in Categorical Data. | Hongzuo Xu, Yongjun Wang, Li Cheng, Yijie Wang, Xingkong Ma |
| 2018 | DEXA | Combine Value Clustering and Weighted Value Coupling Learning for Outlier Detection in Categorical Data. | Hongzuo Xu, Yongjun Wang, Zhiyue Wu, Xingkong Ma, Zhiquan Qin |
| 2017 | CIKM | Selective Value Coupling Learning for Detecting Outliers in High-Dimensional Categorical Data. | Guansong Pang, Hongzuo Xu, Longbing Cao, Wentao Zhao |