Sangkyun Lee
Orcid: 0000-0001-8415-6368Affiliations:
- Hanyang University, ERICA, Ansan, South Korea
- TU Dortmund, Department of Computer Science, Germany (former)
- University of Wisconsin-Madison, Department of Computer Sciences, WI, USA (PhD 2011)
According to our database1,
Sangkyun Lee
authored at least 27 papers
between 2009 and 2024.
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Bibliography
2024
CODE-SMASH: Source-Code Vulnerability Detection Using Siamese and Multi-Level Neural Architecture.
IEEE Access, 2024
Similarity-Based Source Code Vulnerability Detection Leveraging Transformer Architecture: Harnessing Cross- Attention for Hierarchical Analysis.
IEEE Access, 2024
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024
2022
Model Stealing Defense against Exploiting Information Leak through the Interpretation of Deep Neural Nets.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
Libra-CAM: An Activation-Based Attribution Based on the Linear Approximation of Deep Neural Nets and Threshold Calibration.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
2021
Future Internet, 2021
Data Quality Measures and Efficient Evaluation Algorithms for Large-Scale High-Dimensional Data.
CoRR, 2021
IEEE Access, 2021
2019
Structure Learning of Gaussian Markov Random Fields with False Discovery Rate Control.
Symmetry, 2019
CoRR, 2019
2016
Neurocomputing, 2016
Proceedings of the Solving Large Scale Learning Tasks. Challenges and Algorithms, 2016
Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with Ordered L1-Norm.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016
2015
Proceedings of the Feature Selection for Data and Pattern Recognition, 2015
2014
Proceedings of the Interactive Knowledge Discovery and Data Mining in Biomedical Informatics, 2014
Proceedings of the ICPRAM 2014, 2014
Kernel Completion for Learning Consensus Support Vector Machines in Bandwidth-limited Sensor Networks.
Proceedings of the ICPRAM 2014, 2014
Proceedings of the Pattern Recognition Applications and Methods, 2014
Proceedings of the Brain Informatics and Health - International Conference, 2014
2013
Spatio-temporal random fields: compressible representation and distributed estimation.
Mach. Learn., 2013
2012
Manifold Identification in Dual Averaging for Regularized Stochastic Online Learning.
J. Mach. Learn. Res., 2012
Separable Approximate Optimization of Support Vector Machines for Distributed Sensing.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012
Proceedings of the KI 2012: Advances in Artificial Intelligence, 2012
ASSET: Approximate Stochastic Subgradient Estimation Training for Support Vector Machines.
Proceedings of the ICPRAM 2012, 2012
2011
CoRR, 2011
Manifold Identification of Dual Averaging Methods for Regularized Stochastic Online Learning.
Proceedings of the 28th International Conference on Machine Learning, 2011
2009
Decomposition Algorithms for Training Large-Scale Semiparametric Support Vector Machines.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009