Yuejun Guo

Affiliations:
  • University of Luxembourg, Interdisciplinary Centre for Security, Reliability and Trust, Luxembourg
  • University of Girona, Graphics and Imaging Lab, Spain (PhD 2020)
  • Tianjin University, School of Computer Science and Technology, China (2013 - 2016)


According to our database1, Yuejun Guo authored at least 48 papers between 2014 and 2024.

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Timeline

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Bibliography

2024
KAPE: <i>k</i>NN-based Performance Testing for Deep Code Search.
ACM Trans. Softw. Eng. Methodol., February, 2024

LaF: Labeling-free Model Selection for Automated Deep Neural Network Reusing.
ACM Trans. Softw. Eng. Methodol., January, 2024

2023
DRE: density-based data selection with entropy for adversarial-robust deep learning models.
Neural Comput. Appl., February, 2023

An Empirical Study of Deep Learning-Based SS7 Attack Detection.
Inf., 2023

Hazards in Deep Learning Testing: Prevalence, Impact and Recommendations.
CoRR, 2023

Evaluating the Robustness of Test Selection Methods for Deep Neural Networks.
CoRR, 2023

CodeLens: An Interactive Tool for Visualizing Code Representations.
CoRR, 2023

Active Code Learning: Benchmarking Sample-Efficient Training of Code Models.
CoRR, 2023

Boosting Source Code Learning with Data Augmentation: An Empirical Study.
CoRR, 2023

MixCode: Enhancing Code Classification by Mixup-Based Data Augmentation.
Proceedings of the IEEE International Conference on Software Analysis, 2023

Boosting Source Code Learning with Text-Oriented Data Augmentation: An Empirical Study.
Proceedings of the 23rd IEEE International Conference on Software Quality, 2023

MUTEN: Mutant-Based Ensembles for Boosting Gradient-Based Adversarial Attack.
Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering, 2023

CodeS: Towards Code Model Generalization Under Distribution Shift.
Proceedings of the 45th IEEE/ACM International Conference on Software Engineering: New Ideas and Emerging Results, 2023

Aries: Efficient Testing of Deep Neural Networks via Labeling-Free Accuracy Estimation.
Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023

An Investigation of Quality Issues in Vulnerability Detection Datasets.
Proceedings of the IEEE European Symposium on Security and Privacy, 2023

An Empirical Study of the Imbalance Issue in Software Vulnerability Detection.
Proceedings of the Computer Security - ESORICS 2023, 2023

Towards Understanding Model Quantization for Reliable Deep Neural Network Deployment.
Proceedings of the 2nd IEEE/ACM International Conference on AI Engineering, 2023

2022
An Empirical Study on Data Distribution-Aware Test Selection for Deep Learning Enhancement.
ACM Trans. Softw. Eng. Methodol., 2022

Enhancing Mixup-Based Graph Learning for Language Processing via Hybrid Pooling.
CoRR, 2022

Enhancing Code Classification by Mixup-Based Data Augmentation.
CoRR, 2022

Efficient Testing of Deep Neural Networks via Decision Boundary Analysis.
CoRR, 2022

CodeS: A Distribution Shift Benchmark Dataset for Source Code Learning.
CoRR, 2022

Characterizing and Understanding the Behavior of Quantized Models for Reliable Deployment.
CoRR, 2022

Labeling-Free Comparison Testing of Deep Learning Models.
CoRR, 2022

Robust active learning: sample-efficient training of robust deep learning models.
Proceedings of the 1st International Conference on AI Engineering: Software Engineering for AI, 2022

2021
A scalable method to construct compact road networks from GPS trajectories.
Int. J. Geogr. Inf. Sci., 2021

MUTEN: Boosting Gradient-Based Adversarial Attacks via Mutant-Based Ensembles.
CoRR, 2021

Towards Exploring the Limitations of Active Learning: An Empirical Study.
Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering, 2021

2020
Advanced techniques in trajectory data analysis for anomaly detection and map construction.
PhD thesis, 2020

Trajectory Anomaly Detection Based on the Mean Distance Deviation.
Proceedings of the Neural Information Processing - 27th International Conference, 2020

2019
SHNN-CAD<sup>+</sup>: An Improvement on SHNN-CAD for Adaptive Online Trajectory Anomaly Detection.
Sensors, 2019

Detail-Preserving Trajectory Summarization Based on Segmentation and Group-Based Filtering.
Proceedings of the MultiMedia Modeling - 25th International Conference, 2019

Anomaly Detection Based on the Global-Local Anomaly Score for Trajectory Data.
Proceedings of the Neural Information Processing - 26th International Conference, 2019

Eye Movement-Based Analysis on Methodologies and Efficiency in the Process of Image Noise Evaluation.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Image Processing, 2019

2018
A group-based signal filtering approach for trajectory abstraction and restoration.
Neural Comput. Appl., 2018

Random-valued impulse noise removal using adaptive ranked-ordered impulse detector.
J. Electronic Imaging, 2018

IBVis: Interactive Visual Analytics for Information Bottleneck Based Trajectory Clustering.
Entropy, 2018

2017
Trajectory Shape Analysis and Anomaly Detection Utilizing Information Theory Tools .
Entropy, 2017

The Abstraction for Trajectories with Different Numbers of Sampling Points.
Proceedings of the Neural Information Processing - 24th International Conference, 2017

2016
Selecting Video Key Frames Based on Relative Entropy and the Extreme Studentized Deviate Test.
Entropy, 2016

Fast Agglomerative Information Bottleneck Based Trajectory Clustering.
Proceedings of the Neural Information Processing - 23rd International Conference, 2016

2015
3D Visualization of Multiscale Video Key Frames.
Proceedings of the 19th International Conference on Information Visualisation, 2015

Multiscale Visualization of Trajectory Data.
Proceedings of the 19th International Conference on Information Visualisation, 2015

Visualization on Agglomerative Information Bottleneck Based Trajectory Clustering.
Proceedings of the 19th International Conference on Information Visualisation, 2015

Trajectory Abstracting with Group-Based Signal Denoising.
Proceedings of the Neural Information Processing - 22nd International Conference, 2015

XaIBO: An Extension of aIB for Trajectory Clustering with Outlier.
Proceedings of the Neural Information Processing - 22nd International Conference, 2015

A mixed noise removal algorithm based on the maximum entropy principle.
Proceedings of the 2015 IEEE International Conference on Multimedia and Expo, 2015

2014
A New Scheme for Trajectory Visualization.
Proceedings of the 18th International Conference on Information Visualisation, 2014


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