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ORCIDSangkyun Lee 0002
Person information
- affiliation: Hanyang University, ERICA, Ansan, South Korea
- affiliation (former): TU Dortmund, Department of Computer Science, Germany
- affiliation (PhD 2011): University of Wisconsin-Madison, Department of Computer Sciences, WI, USA
Other persons with the same name
- Sangkyun Lee — disambiguation page
- Sangkyun Lee 0001 — Max Planck Institute for Biological Cybernetics, Tübingen
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2020 – today
- 2024
[j8]Sungmin Han
, Hyunkyung Nam, Jaesik Kang, Kwangsoo Kim, Seungjae Cho, Sangkyun Lee:
CODE-SMASH: Source-Code Vulnerability Detection Using Siamese and Multi-Level Neural Architecture. IEEE Access 12: 102492-102504 (2024)- [j7]Sungmin Han, Miju Kim, Jaesik Kang, Kwangsoo Kim, Seungwoon Lee, Sangkyun Lee:
Similarity-Based Source Code Vulnerability Detection Leveraging Transformer Architecture: Harnessing Cross- Attention for Hierarchical Analysis. IEEE Access 12: 150295-150307 (2024) - [c14]Jeonghyun Lee, Sungmin Han, Sangkyun Lee:
SwiftThief: Enhancing Query Efficiency of Model Stealing by Contrastive Learning. IJCAI 2024: 422-430 - 2022
- [c13]Jeonghyun Lee, Sungmin Han, Sangkyun Lee:
Model Stealing Defense against Exploiting Information Leak through the Interpretation of Deep Neural Nets. IJCAI 2022: 710-716 - [c12]Sangkyun Lee, Sungmin Han:
Libra-CAM: An Activation-Based Attribution Based on the Linear Approximation of Deep Neural Nets and Threshold Calibration. IJCAI 2022: 3185-3191 - 2021
- [j6]Seongyun Seo, Sungmin Han, Janghyeon Park, Shin-Woo Shim, Han-Eul Ryu, Byoungmo Cho, Sangkyun Lee:
Hunt for Unseen Intrusion: Multi-Head Self-Attention Neural Detector. IEEE Access 9: 129635-129647 (2021) - [j5]Junhyung Kwon, Sangkyun Lee:
Improving the Robustness of Model Compression by On-Manifold Adversarial Training. Future Internet 13(12): 300 (2021) - [i4]Hyeongmin Cho, Sangkyun Lee:
Data Quality Measures and Efficient Evaluation Algorithms for Large-Scale High-Dimensional Data. CoRR abs/2101.01441 (2021)
2010 – 2019
- 2019
- [j4]Sangkyun Lee, Piotr Sobczyk, Malgorzata Bogdan:
Structure Learning of Gaussian Markov Random Fields with False Discovery Rate Control. Symmetry 11(10): 1311 (2019) - [i3]Sangkyun Lee, Jeonghyun Lee:
Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems. CoRR abs/1905.07931 (2019) - [i2]Sangkyun Lee, Piotr Sobczyk, Malgorzata Bogdan:
Structure Learning of Gaussian Markov Random Fields with False Discovery Rate Control. CoRR abs/1910.10860 (2019) - 2016
- [j3]Nico Piatkowski, Sangkyun Lee, Katharina Morik:
Integer undirected graphical models for resource-constrained systems. Neurocomputing 173: 9-23 (2016) - [c11]Sangkyun Lee, Damian Brzyski, Malgorzata Bogdan:
Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with Ordered L1-Norm. AISTATS 2016: 780-789 - [c10]Sangkyun Lee, Andreas Holzinger:
Knowledge Discovery from Complex High Dimensional Data. Solving Large Scale Learning Tasks 2016: 148-167 - 2015
- [p2]Sangkyun Lee:
Signature Selection for Grouped Features with a Case Study on Exon Microarrays. Feature Selection for Data and Pattern Recognition 2015: 329-349 - 2014
- [c9]Sangkyun Lee:
Characterization of Subgroup Patterns from Graphical Representation of Genomic Data. Brain Informatics and Health 2014: 516-527 - [c8]Sangkyun Lee, Christian Pölitz:
Kernel Matrix Completion for Learning Nearly Consensus Support Vector Machines. ICPRAM (Selected Papers) 2014: 93-109 - [c7]Sangkyun Lee, Christian Pölitz:
Kernel Completion for Learning Consensus Support Vector Machines in Bandwidth-limited Sensor Networks. ICPRAM 2014: 113-124 - [c6]Nico Piatkowski, Sangkyun Lee, Katharina Morik:
The Integer Approximation of Undirected Graphical Models. ICPRAM 2014: 296-304 - [p1]Sangkyun Lee:
Sparse Inverse Covariance Estimation for Graph Representation of Feature Structure. Interactive Knowledge Discovery and Data Mining in Biomedical Informatics 2014: 227-240 - 2013
- [j2]Nico Piatkowski, Sangkyun Lee, Katharina Morik:
Spatio-temporal random fields: compressible representation and distributed estimation. Mach. Learn. 93(1): 115-139 (2013) - 2012
- [j1]Sangkyun Lee, Stephen J. Wright:
Manifold Identification in Dual Averaging for Regularized Stochastic Online Learning. J. Mach. Learn. Res. 13: 1705-1744 (2012) - [c5]Sangkyun Lee, Stephen J. Wright:
ASSET: Approximate Stochastic Subgradient Estimation Training for Support Vector Machines. ICPRAM (1) 2012: 223-228 - [c4]Sangkyun Lee:
Improving Confidence of Dual Averaging Stochastic Online Learning via Aggregation. KI 2012: 229-232 - [c3]Sangkyun Lee, Marco Stolpe, Katharina Morik:
Separable Approximate Optimization of Support Vector Machines for Distributed Sensing. ECML/PKDD (2) 2012: 387-402 - 2011
- [c2]Sangkyun Lee, Stephen J. Wright:
Manifold Identification of Dual Averaging Methods for Regularized Stochastic Online Learning. ICML 2011: 1121-1128 - [i1]Sangkyun Lee, Stephen J. Wright:
Approximate Stochastic Subgradient Estimation Training for Support Vector Machines. CoRR abs/1111.0432 (2011)
2000 – 2009
- 2009
- [c1]Sangkyun Lee, Stephen J. Wright:
Decomposition Algorithms for Training Large-Scale Semiparametric Support Vector Machines. ECML/PKDD (2) 2009: 1-14
Coauthor Index
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