2025
Deep anomaly detection with partition contrastive learning for tabular data.
Data Min. Knowl. Discov., July, 2025
2024
Calibrated One-Class Classification for Unsupervised Time Series Anomaly Detection.
IEEE Trans. Knowl. Data Eng., November, 2024
Angel or Devil: Discriminating Hard Samples and Anomaly Contaminations for Unsupervised Time Series Anomaly Detection.
CoRR, 2024
Abnormality Forecasting: Time Series Anomaly Prediction via Future Context Modeling.
CoRR, 2024
Self-supervised Spatial-Temporal Normality Learning for Time Series Anomaly Detection.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024
Hierarchical Adaptive Pooling by Capturing High-order Dependency for Graph Representation Learning (Extended Abstract).
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024
Boundary-Driven Active Learning for Anomaly Detection in Time Series Data Streams.
Proceedings of the IEEE International Conference on Acoustics, 2024
2023
Deep Isolation Forest for Anomaly Detection.
IEEE Trans. Knowl. Data Eng., December, 2023
RoSAS: Deep semi-supervised anomaly detection with contamination-resilient continuous supervision.
Inf. Process. Manag., September, 2023
Hierarchical Adaptive Pooling by Capturing High-Order Dependency for Graph Representation Learning.
IEEE Trans. Knowl. Data Eng., April, 2023
Local-Adaptive Transformer for Multivariate Time Series Anomaly Detection and Diagnosis.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2023
Multi-Scale Sampling Based MLP Networks for Anomaly Detection in Multivariate Time Series.
Proceedings of the 29th IEEE International Conference on Parallel and Distributed Systems, 2023
Fascinating Supervisory Signals and Where to Find Them: Deep Anomaly Detection with Scale Learning.
Proceedings of the International Conference on Machine Learning, 2023
Deep Reinforced Active Learning for Time Series Anomaly Detection.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023
Smoothing Point Adjustment-Based Evaluation of Time Series Anomaly Detection.
Proceedings of the IEEE International Conference on Acoustics, 2023
2022
Factorization Machine-based Unsupervised Model Selection Method<sup>*</sup>.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2022
DPSS: Dynamic Parameter Selection for Outlier Detection on Data Streams.
Proceedings of the 28th IEEE International Conference on Parallel and Distributed Systems, 2022
Unsupervised Hierarchical Graph Pooling via Substructure-Sensitive Mutual Information Maximization.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
2021
DRAM Failure Prediction in AIOps: EmpiricalEvaluation, Challenges and Opportunities.
CoRR, 2021
Few-shot website fingerprinting attack.
Comput. Networks, 2021
Beyond Outlier Detection: Outlier Interpretation by Attention-Guided Triplet Deviation Network.
Proceedings of the WWW '21: The Web Conference 2021, 2021
Surrogate Supervision-based Deep Weakly-supervised Anomaly Detection.
Proceedings of the 2021 International Conference on Data Mining, 2021
Integrating Argument-Level Attention with Multi-Level Scores to Predict What Happen Next.
Proceedings of the International Joint Conference on Neural Networks, 2021
Effective Anomaly Detection Based on Reinforcement Learning in Network Traffic Data.
Proceedings of the 27th IEEE International Conference on Parallel and Distributed Systems, 2021
OADA: An Online Data Augmentation Method for Raw Histopathology Images.
Proceedings of the Neural Information Processing - 28th International Conference, 2021
Script event prediction based on pre-trained model with tail event enhancement.
Proceedings of the CSAI 2021: 5th International Conference on Computer Science and Artificial Intelligence, Beijing, China, December 4, 2021
2020
Tree2tree Structural Language Modeling for Compiler Fuzzing.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2020
2019
MIX: A Joint Learning Framework for Detecting Both Clustered and Scattered Outliers in Mixed-Type Data.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019
Embedding-Based Complex Feature Value Coupling Learning for Detecting Outliers in Non-IID Categorical Data.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
2018
Combine Value Clustering and Weighted Value Coupling Learning for Outlier Detection in Categorical Data.
Proceedings of the Database and Expert Systems Applications, 2018
Exploring a High-quality Outlying Feature Value Set for Noise-Resilient Outlier Detection in Categorical Data.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018
2017
Selective Value Coupling Learning for Detecting Outliers in High-Dimensional Categorical Data.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017