Hongzuo Xu

Orcid: 0000-0001-8074-1244

According to our database1, Hongzuo Xu authored at least 29 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Calibrated One-Class Classification for Unsupervised Time Series Anomaly Detection.
IEEE Trans. Knowl. Data Eng., November, 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


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