Sangkyun Lee - RankMe

30 papers A* 4A 1C 2Misc 1Journal 14Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	SQL Injection in LLM-Generated Queries: Systematic Analysis of Detection Gaps and Security Risks. IEEE Access Eunyoung Kim, Sangkyun Lee
2025	J	`jnl`	CERBEROS: Compression-Based Efficient and Robust Optimized Security for Model Stealing Defense. IEEE Access Sohyun Keum, Jeonghyun Lee, Sangkyun Lee
2024	J	`jnl`	CODE-SMASH: Source-Code Vulnerability Detection Using Siamese and Multi-Level Neural Architecture. IEEE Access Sungmin Han, Hyunkyung Nam, Jaesik Kang, Kwangsoo Kim, Seungjae Cho, Sangkyun Lee
2024	J	`jnl`	Similarity-Based Source Code Vulnerability Detection Leveraging Transformer Architecture: Harnessing Cross- Attention for Hierarchical Analysis. IEEE Access Sungmin Han, Miju Kim, Jaesik Kang, Kwangsoo Kim, Seungwoon Lee, Sangkyun Lee
2024	A*	`conf`	SwiftThief: Enhancing Query Efficiency of Model Stealing by Contrastive Learning. IJCAI Jeonghyun Lee, Sungmin Han, Sangkyun Lee
2022	A*	`conf`	Libra-CAM: An Activation-Based Attribution Based on the Linear Approximation of Deep Neural Nets and Threshold Calibration. IJCAI Sangkyun Lee, Sungmin Han
2022	A*	`conf`	Model Stealing Defense against Exploiting Information Leak through the Interpretation of Deep Neural Nets. IJCAI Jeonghyun Lee, Sungmin Han, Sangkyun Lee
2021	J	`jnl`	Data Quality Measures and Efficient Evaluation Algorithms for Large-Scale High-Dimensional Data. CoRR Hyeongmin Cho, Sangkyun Lee
2021	J	`jnl`	Hunt for Unseen Intrusion: Multi-Head Self-Attention Neural Detector. IEEE Access Seongyun Seo, Sungmin Han, Janghyeon Park, Shin-Woo Shim, Han-Eul Ryu, Byoungmo Cho, Sangkyun Lee
2021	J	`jnl`	Improving the Robustness of Model Compression by On-Manifold Adversarial Training. Future Internet Junhyung Kwon, Sangkyun Lee
2019	J	`jnl`	Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems. CoRR Sangkyun Lee, Jeonghyun Lee
2019	J	`jnl`	Structure Learning of Gaussian Markov Random Fields with False Discovery Rate Control. CoRR Sangkyun Lee, Piotr Sobczyk, Malgorzata Bogdan
2019	J	`jnl`	Structure Learning of Gaussian Markov Random Fields with False Discovery Rate Control. Symmetry Sangkyun Lee, Piotr Sobczyk, Malgorzata Bogdan
2016	A	`conf`	Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with Ordered L1-Norm. AISTATS Sangkyun Lee, Damian Brzyski, Malgorzata Bogdan
2016	J	`jnl`	Integer undirected graphical models for resource-constrained systems. Neurocomputing Nico Piatkowski, Sangkyun Lee, Katharina Morik
2016	—	`conf`	Knowledge Discovery from Complex High Dimensional Data. Solving Large Scale Learning Tasks Sangkyun Lee, Andreas Holzinger
2015	—	`ch.`	Signature Selection for Grouped Features with a Case Study on Exon Microarrays. Feature Selection for Data and Pattern Recognition Sangkyun Lee
2014	—	`conf`	Characterization of Subgroup Patterns from Graphical Representation of Genomic Data. Brain Informatics and Health Sangkyun Lee
2014	C	`conf`	Kernel Completion for Learning Consensus Support Vector Machines in Bandwidth-limited Sensor Networks. ICPRAM Sangkyun Lee, Christian Pölitz
2014	—	`conf`	Kernel Matrix Completion for Learning Nearly Consensus Support Vector Machines. ICPRAM (Selected Papers) Sangkyun Lee, Christian Pölitz
2014	—	`ch.`	Sparse Inverse Covariance Estimation for Graph Representation of Feature Structure. Interactive Knowledge Discovery and Data Mining in Biomedical Informatics Sangkyun Lee
2014	C	`conf`	The Integer Approximation of Undirected Graphical Models. ICPRAM Nico Piatkowski, Sangkyun Lee, Katharina Morik
2013	J	`jnl`	Spatio-temporal random fields: compressible representation and distributed estimation. Mach. Learn. Nico Piatkowski, Sangkyun Lee, Katharina Morik
2012	—	`conf`	ASSET: Approximate Stochastic Subgradient Estimation Training for Support Vector Machines. ICPRAM (1) Sangkyun Lee, Stephen J. Wright
2012	Misc	`conf`	Improving Confidence of Dual Averaging Stochastic Online Learning via Aggregation. KI Sangkyun Lee
2012	J	`jnl`	Manifold Identification in Dual Averaging for Regularized Stochastic Online Learning. J. Mach. Learn. Res. Sangkyun Lee, Stephen J. Wright
2012	—	`conf`	Separable Approximate Optimization of Support Vector Machines for Distributed Sensing. ECML/PKDD (2) Sangkyun Lee, Marco Stolpe, Katharina Morik
2011	J	`jnl`	Approximate Stochastic Subgradient Estimation Training for Support Vector Machines CoRR Sangkyun Lee, Stephen J. Wright
2011	A*	`conf`	Manifold Identification of Dual Averaging Methods for Regularized Stochastic Online Learning. ICML Sangkyun Lee, Stephen J. Wright
2009	—	`conf`	Decomposition Algorithms for Training Large-Scale Semiparametric Support Vector Machines. ECML/PKDD (2) Sangkyun Lee, Stephen J. Wright