Sangkyun Lee

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 12

Top Topics

Support Vector Machine

Dimensional Data

Graphical Models

Top Venues

Publications

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 (2024)
Sangkyun Lee, Sungmin Han
Libra-CAM: An Activation-Based Attribution Based on the Linear Approximation of Deep Neural Nets and Threshold Calibration. IJCAI (2022)
Jeonghyun Lee, Sungmin Han, Sangkyun Lee
Model Stealing Defense against Exploiting Information Leak through the Interpretation of Deep Neural Nets. IJCAI (2022)
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 (2021)
Hyeongmin Cho, Sangkyun Lee
Data Quality Measures and Efficient Evaluation Algorithms for Large-Scale High-Dimensional Data. CoRR (2021)
Junhyung Kwon, Sangkyun Lee
Improving the Robustness of Model Compression by On-Manifold Adversarial Training. Future Internet 13 (12) (2021)
Sangkyun Lee, Piotr Sobczyk, Malgorzata Bogdan
Structure Learning of Gaussian Markov Random Fields with False Discovery Rate Control. Symmetry 11 (10) (2019)
Sangkyun Lee, Jeonghyun Lee
Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems. CoRR (2019)
Sangkyun Lee, Piotr Sobczyk, Malgorzata Bogdan
Structure Learning of Gaussian Markov Random Fields with False Discovery Rate Control. CoRR (2019)
Sangkyun Lee, Andreas Holzinger
Knowledge Discovery from Complex High Dimensional Data. Solving Large Scale Learning Tasks (2016)
Sangkyun Lee, Damian Brzyski, Malgorzata Bogdan
Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with Ordered L1-Norm. AISTATS (2016)
Nico Piatkowski, Sangkyun Lee, Katharina Morik
Integer undirected graphical models for resource-constrained systems. Neurocomputing 173 (2016)
Sangkyun Lee
Characterization of Subgroup Patterns from Graphical Representation of Genomic Data. Brain Informatics and Health (2014)
Sangkyun Lee, Christian Pölitz
Kernel Completion for Learning Consensus Support Vector Machines in Bandwidth-limited Sensor Networks. ICPRAM (2014)
Nico Piatkowski, Sangkyun Lee, Katharina Morik
The Integer Approximation of Undirected Graphical Models. ICPRAM (2014)
Sangkyun Lee, Christian Pölitz
Kernel Matrix Completion for Learning Nearly Consensus Support Vector Machines. ICPRAM (Selected Papers) (2014)
Nico Piatkowski, Sangkyun Lee, Katharina Morik
Spatio-temporal random fields: compressible representation and distributed estimation. Mach. Learn. 93 (1) (2013)
Sangkyun Lee, Marco Stolpe, Katharina Morik
Separable Approximate Optimization of Support Vector Machines for Distributed Sensing. ECML/PKDD (2) (2012)
Sangkyun Lee, Stephen J. Wright
Manifold Identification in Dual Averaging for Regularized Stochastic Online Learning. J. Mach. Learn. Res. 13 (2012)
Sangkyun Lee
Improving Confidence of Dual Averaging Stochastic Online Learning via Aggregation. KI (2012)
Sangkyun Lee, Stephen J. Wright
ASSET: Approximate Stochastic Subgradient Estimation Training for Support Vector Machines. ICPRAM (1) (2012)
Sangkyun Lee, Stephen J. Wright
Approximate Stochastic Subgradient Estimation Training for Support Vector Machines CoRR (2011)
Sangkyun Lee, Stephen J. Wright
Manifold Identification of Dual Averaging Methods for Regularized Stochastic Online Learning. ICML (2011)
Sangkyun Lee, Stephen J. Wright
Decomposition Algorithms for Training Large-Scale Semiparametric Support Vector Machines. ECML/PKDD (2) (2009)