Decomposition Algorithms for Training Large-Scale Semiparametric Support Vector Machines. - Sangkyun Lee 002; Stephen J. Wright 001 (ECML/PKDD (2), 2009)

Manifold Identification of Dual Averaging Methods for Regularized Stochastic Online Learning. - Sangkyun Lee 002; Stephen J. Wright 001 (ICML, 2011)

Approximate Stochastic Subgradient Estimation Training for Support Vector Machines - Sangkyun Lee 002; Stephen J. Wright 001 (CoRR, 2011)

ASSET: Approximate Stochastic Subgradient Estimation Training for Support Vector Machines. - Sangkyun Lee 002; Stephen J. Wright 001 (ICPRAM (1), 2012)

Improving Confidence of Dual Averaging Stochastic Online Learning via Aggregation. - Sangkyun Lee 002 (KI, 2012)

Separable Approximate Optimization of Support Vector Machines for Distributed Sensing. - Sangkyun Lee 002; Marco Stolpe; Katharina Morik (ECML/PKDD (2), 2012)

Manifold Identification in Dual Averaging for Regularized Stochastic Online Learning. - Sangkyun Lee 002; Stephen J. Wright 001 (J. Mach. Learn. Res., 2012)

Spatio-temporal random fields: compressible representation and distributed estimation. - Nico Piatkowski; Sangkyun Lee 002; Katharina Morik (Mach. Learn., 2013)

Characterization of Subgroup Patterns from Graphical Representation of Genomic Data. - Sangkyun Lee 002 (Brain Informatics and Health, 2014)

Kernel Matrix Completion for Learning Nearly Consensus Support Vector Machines. - Sangkyun Lee 002; Christian Pölitz (ICPRAM (Selected Papers), 2014)

Kernel Completion for Learning Consensus Support Vector Machines in Bandwidth-limited Sensor Networks. - Sangkyun Lee 002; Christian Pölitz (ICPRAM, 2014)

The Integer Approximation of Undirected Graphical Models. - Nico Piatkowski; Sangkyun Lee 002; Katharina Morik (ICPRAM, 2014)

Sparse Inverse Covariance Estimation for Graph Representation of Feature Structure. - Sangkyun Lee 002 (Interactive Knowledge Discovery and Data Mining in Biomedical Informatics, 2014)

Signature Selection for Grouped Features with a Case Study on Exon Microarrays. - Sangkyun Lee 002 (Feature Selection for Data and Pattern Recognition, 2015)

Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with Ordered L1-Norm. - Sangkyun Lee 002; Damian Brzyski; Malgorzata Bogdan (AISTATS, 2016)

Knowledge Discovery from Complex High Dimensional Data. - Sangkyun Lee 002; Andreas Holzinger (Solving Large Scale Learning Tasks, 2016)

Integer undirected graphical models for resource-constrained systems. - Nico Piatkowski; Sangkyun Lee 002; Katharina Morik (Neurocomputing, 2016)

Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems. - Sangkyun Lee 002; Jeonghyun Lee (CoRR, 2019)

Structure Learning of Gaussian Markov Random Fields with False Discovery Rate Control. - Sangkyun Lee 002; Piotr Sobczyk; Malgorzata Bogdan (Symmetry, 2019)

Hunt for Unseen Intrusion: Multi-Head Self-Attention Neural Detector. - Seongyun Seo; Sungmin Han; Janghyeon Park; Shin-Woo Shim; Han-Eul Ryu; Byoungmo Cho; Sangkyun Lee 002 (IEEE Access, 2021)

Data Quality Measures and Efficient Evaluation Algorithms for Large-Scale High-Dimensional Data. - Hyeongmin Cho; Sangkyun Lee 002 (CoRR, 2021)

Improving the Robustness of Model Compression by On-Manifold Adversarial Training. - Junhyung Kwon; Sangkyun Lee 002 (Future Internet, 2021)

Libra-CAM: An Activation-Based Attribution Based on the Linear Approximation of Deep Neural Nets and Threshold Calibration. - Sangkyun Lee 002; Sungmin Han (IJCAI, 2022)

Model Stealing Defense against Exploiting Information Leak through the Interpretation of Deep Neural Nets. - Jeonghyun Lee; Sungmin Han; Sangkyun Lee 002 (IJCAI, 2022)

SwiftThief: Enhancing Query Efficiency of Model Stealing by Contrastive Learning. - Jeonghyun Lee; Sungmin Han; Sangkyun Lee 002 (IJCAI, 2024)

Similarity-Based Source Code Vulnerability Detection Leveraging Transformer Architecture: Harnessing Cross- Attention for Hierarchical Analysis. - Sungmin Han; Miju Kim; Jaesik Kang; Kwangsoo Kim; Seungwoon Lee; Sangkyun Lee 002 (IEEE Access, 2024)

CODE-SMASH: Source-Code Vulnerability Detection Using Siamese and Multi-Level Neural Architecture. - Sungmin Han; Hyunkyung Nam; Jaesik Kang; Kwangsoo Kim; Seungjae Cho; Sangkyun Lee 002 (IEEE Access, 2024)