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Yuejun Guo 0001
Person information
- affiliation: University of Luxembourg, Interdisciplinary Centre for Security, Reliability and Trust, Luxembourg
- affiliation (PhD 2020): University of Girona, Graphics and Imaging Lab, Spain
- affiliation (2013 - 2016): Tianjin University, School of Computer Science and Technology, China
Other persons with the same name
- Yuejun Guo 0002
— Dalian Maritime University, Navigation College, China
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2020 – today
- 2024
- [j17]Xueqi Dang, Yinghua Li
Towards Exploring the Limitations of Test Selection Techniques on Graph Neural Networks: An Empirical Study. Empir. Softw. Eng. 29(5): 112 (2024) - [j16]Yuejun Guo, Seifeddine Bettaieb, Fran Casino:
A comprehensive analysis on software vulnerability detection datasets: trends, challenges, and road ahead. Int. J. Inf. Sec. 23(5): 3311-3327 (2024) - [j15]Zeming Dong
On the effectiveness of hybrid pooling in mixup-based graph learning for language processing. J. Syst. Softw. 216: 112139 (2024) - [j14]Qiang Hu
LaF: Labeling-free Model Selection for Automated Deep Neural Network Reusing. ACM Trans. Softw. Eng. Methodol. 33(1): 25:1-25:28 (2024) - [j13]Yuejun Guo
KAPE: kNN-based Performance Testing for Deep Code Search. ACM Trans. Softw. Eng. Methodol. 33(2): 48:1-48:24 (2024) - [j12]Qiang Hu
Test Optimization in DNN Testing: A Survey. ACM Trans. Softw. Eng. Methodol. 33(4): 111:1-111:42 (2024) - [j11]Qiang Hu
Active Code Learning: Benchmarking Sample-Efficient Training of Code Models. IEEE Trans. Software Eng. 50(5): 1080-1095 (2024) - [c25]Wanpeng Li, Yuejun Guo:
Poster: Automated Dependency Mapping for Web API Security Testing Using Large Language Models. CCS 2024: 5024-5026 - [c24]Yuejun Guo
Outside the Comfort Zone: Analysing LLM Capabilities in Software Vulnerability Detection. ESORICS (1) 2024: 271-289 - [i16]Yuejun Guo, Constantinos Patsakis, Qiang Hu, Qiang Tang, Fran Casino:
Outside the Comfort Zone: Analysing LLM Capabilities in Software Vulnerability Detection. CoRR abs/2408.16400 (2024) - [i15]Yuejun Guo, Seifeddine Bettaieb:
Data Quality Issues in Vulnerability Detection Datasets. CoRR abs/2410.06030 (2024) - [i14]Aayush Garg, Yuejun Guo, Qiang Tang:
AI-Driven Software Security: Vulnerability Detection, Patching, and Anti-Fuzzing. ERCIM News 139(138) (2024) - 2023
- [j10]Yuejun Guo
An Empirical Study of Deep Learning-Based SS7 Attack Detection. Inf. 14(9): 509 (2023) - [j9]Yuejun Guo
DRE: density-based data selection with entropy for adversarial-robust deep learning models. Neural Comput. Appl. 35(5): 4009-4026 (2023) - [c23]Qiang Hu, Yuejun Guo, Maxime Cordy, Xiaofei Xie, Wei Ma, Mike Papadakis, Yves Le Traon:
Towards Understanding Model Quantization for Reliable Deep Neural Network Deployment. CAIN 2023: 56-67 - [c22]Yuejun Guo
An Empirical Study of the Imbalance Issue in Software Vulnerability Detection. ESORICS (4) 2023: 371-390 - [c21]Yuejun Guo, Seifeddine Bettaieb:
An Investigation of Quality Issues in Vulnerability Detection Datasets. EuroS&P Workshops 2023: 29-33 - [c20]Qiang Hu, Yuejun Guo, Xiaofei Xie
CodeS: Towards Code Model Generalization Under Distribution Shift. ICSE (NIER) 2023: 1-6 - [c19]Qiang Hu, Yuejun Guo, Xiaofei Xie
Aries: Efficient Testing of Deep Neural Networks via Labeling-Free Accuracy Estimation. ICSE 2023: 1776-1787 - [c18]Qiang Hu, Yuejun Guo, Maxime Cordy, Mike Papadakis, Yves Le Traon:
MUTEN: Mutant-Based Ensembles for Boosting Gradient-Based Adversarial Attack. ASE 2023: 1708-1712 - [c17]Zeming Dong, Qiang Hu, Yuejun Guo, Zhenya Zhang, Jianjun Zhao:
Boosting Source Code Learning with Text-Oriented Data Augmentation: An Empirical Study. QRS Companion 2023: 383-392 - [c16]Zeming Dong
MixCode: Enhancing Code Classification by Mixup-Based Data Augmentation. SANER 2023: 379-390 - [i13]Zeming Dong, Qiang Hu, Yuejun Guo, Zhenya Zhang, Maxime Cordy, Mike Papadakis, Yves Le Traon, Jianjun Zhao:
Boosting Source Code Learning with Data Augmentation: An Empirical Study. CoRR abs/2303.06808 (2023) - [i12]Qiang Hu, Yuejun Guo, Xiaofei Xie, Maxime Cordy, Lei Ma, Mike Papadakis, Yves Le Traon:
Active Code Learning: Benchmarking Sample-Efficient Training of Code Models. CoRR abs/2306.01250 (2023) - [i11]Yuejun Guo, Seifeddine Bettaieb, Qiang Hu, Yves Le Traon, Qiang Tang:
CodeLens: An Interactive Tool for Visualizing Code Representations. CoRR abs/2307.14902 (2023) - [i10]Qiang Hu, Yuejun Guo, Xiaofei Xie, Maxime Cordy, Wei Ma, Mike Papadakis, Yves Le Traon:
Evaluating the Robustness of Test Selection Methods for Deep Neural Networks. CoRR abs/2308.01314 (2023) - [i9]Salah Ghamizi, Maxime Cordy, Yuejun Guo, Mike Papadakis, Yves Le Traon:
Hazards in Deep Learning Testing: Prevalence, Impact and Recommendations. CoRR abs/2309.05381 (2023) - 2022
- [j8]Qiang Hu
An Empirical Study on Data Distribution-Aware Test Selection for Deep Learning Enhancement. ACM Trans. Softw. Eng. Methodol. 31(4): 78:1-78:30 (2022) - [c15]Yuejun Guo, Qiang Hu, Maxime Cordy, Mike Papadakis, Yves Le Traon:
Robust active learning: sample-efficient training of robust deep learning models. CAIN 2022: 41-42 - [i8]Yuejun Guo, Qiang Hu, Maxime Cordy, Xiaofei Xie, Mike Papadakis
Labeling-Free Comparison Testing of Deep Learning Models. CoRR abs/2204.03994 (2022) - [i7]Qiang Hu, Yuejun Guo, Maxime Cordy, Xiaofei Xie, Wei Ma, Mike Papadakis
Characterizing and Understanding the Behavior of Quantized Models for Reliable Deployment. CoRR abs/2204.04220 (2022) - [i6]Qiang Hu, Yuejun Guo, Xiaofei Xie, Maxime Cordy, Lei Ma, Mike Papadakis, Yves Le Traon:
CodeS: A Distribution Shift Benchmark Dataset for Source Code Learning. CoRR abs/2206.05480 (2022) - [i5]Qiang Hu, Yuejun Guo, Xiaofei Xie, Maxime Cordy, Lei Ma, Mike Papadakis, Yves Le Traon:
Efficient Testing of Deep Neural Networks via Decision Boundary Analysis. CoRR abs/2207.10942 (2022) - [i4]Zeming Dong, Qiang Hu, Yuejun Guo, Maxime Cordy, Mike Papadakis, Yves Le Traon, Jianjun Zhao:
Enhancing Code Classification by Mixup-Based Data Augmentation. CoRR abs/2210.03003 (2022) - [i3]Zeming Dong, Qiang Hu, Yuejun Guo, Maxime Cordy, Mike Papadakis, Yves Le Traon, Jianjun Zhao:
Enhancing Mixup-Based Graph Learning for Language Processing via Hybrid Pooling. CoRR abs/2210.03123 (2022) - 2021
- [j7]Yuejun Guo
A scalable method to construct compact road networks from GPS trajectories. Int. J. Geogr. Inf. Sci. 35(7): 1309-1345 (2021) - [c14]Qiang Hu, Yuejun Guo
Towards Exploring the Limitations of Active Learning: An Empirical Study. ASE 2021: 917-929 - [i2]Yuejun Guo, Qiang Hu, Maxime Cordy, Michail Papadakis, Yves Le Traon:
MUTEN: Boosting Gradient-Based Adversarial Attacks via Mutant-Based Ensembles. CoRR abs/2109.12838 (2021) - [i1]Yuejun Guo, Qiang Hu, Maxime Cordy, Mike Papadakis, Yves Le Traon:
Robust Active Learning: Sample-Efficient Training of Robust Deep Learning Models. CoRR abs/2112.02542 (2021) - 2020
- [b1]Yuejun Guo:
Advanced techniques in trajectory data analysis for anomaly detection and map construction. University of Girona, Spain, 2020 - [c13]Xiaoyuan Hu, Qing Xu, Yuejun Guo
Trajectory Anomaly Detection Based on the Mean Distance Deviation. ICONIP (4) 2020: 140-147
2010 – 2019
- 2019
- [j6]Yuejun Guo
SHNN-CAD+: An Improvement on SHNN-CAD for Adaptive Online Trajectory Anomaly Detection. Sensors 19(1): 84 (2019) - [c12]Cheng Peng, Qing Xu
Eye Movement-Based Analysis on Methodologies and Efficiency in the Process of Image Noise Evaluation. ICANN (3) 2019: 29-40 - [c11]Chengcheng Li, Qing Xu, Cheng Peng, Yuejun Guo
Anomaly Detection Based on the Global-Local Anomaly Score for Trajectory Data. ICONIP (5) 2019: 275-285 - [c10]Ting Wu, Qing Xu, Yunhe Li, Yuejun Guo
Detail-Preserving Trajectory Summarization Based on Segmentation and Group-Based Filtering. MMM (2) 2019: 402-413 - 2018
- [j5]Yuejun Guo
IBVis: Interactive Visual Analytics for Information Bottleneck Based Trajectory Clustering. Entropy 20(3): 159 (2018) - [j4]Qing Xu, Yunhe Li, Yuejun Guo
Random-valued impulse noise removal using adaptive ranked-ordered impulse detector. J. Electronic Imaging 27(1): 13001 (2018) - [j3]Yuejun Guo
A group-based signal filtering approach for trajectory abstraction and restoration. Neural Comput. Appl. 29(9): 371-387 (2018) - 2017
- [j2]Yuejun Guo
Trajectory Shape Analysis and Anomaly Detection Utilizing Information Theory Tools . Entropy 19(7): 323 (2017) - [c9]Peng Li, Qing Xu, Hao Wei, Yuejun Guo
The Abstraction for Trajectories with Different Numbers of Sampling Points. ICONIP (6) 2017: 434-442 - 2016
- [j1]Yuejun Guo
Selecting Video Key Frames Based on Relative Entropy and the Extreme Studentized Deviate Test. Entropy 18(3): 73 (2016) - [c8]Yuejun Guo
Fast Agglomerative Information Bottleneck Based Trajectory Clustering. ICONIP (3) 2016: 425-433 - 2015
- [c7]Shang Wu, Qing Xu, Jialang Li, Yuejun Guo
A mixed noise removal algorithm based on the maximum entropy principle. ICME 2015: 1-6 - [c6]Yuejun Guo
XaIBO: An Extension of aIB for Trajectory Clustering with Outlier. ICONIP (2) 2015: 423-431 - [c5]Xiaoxiao Luo, Qing Xu, Yuejun Guo
Trajectory Abstracting with Group-Based Signal Denoising. ICONIP (3) 2015: 452-461 - [c4]Sheng Liang, Qing Xu, Yuejun Guo
Multiscale Visualization of Trajectory Data. IV 2015: 206-210 - [c3]Shihua Sun, Qing Xu, Yuejun Guo
3D Visualization of Multiscale Video Key Frames. IV 2015: 223-227 - [c2]Yang Fan, Qing Xu, Yuejun Guo
Visualization on Agglomerative Information Bottleneck Based Trajectory Clustering. IV 2015: 557-560 - 2014
- [c1]Yuejun Guo
A New Scheme for Trajectory Visualization. IV 2014: 40-45
Coauthor Index
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last updated on 2024-12-11 20:47 CET by the dblp team
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