| LinkSCAN*: Overlapping Community Detection Using the Link-Space Transformation S Lim, S Ryu, S Kwon, K Jung, JG Lee IEEE International Conference on Data Engineering (ICDE), 292-303, 2014 | 100 | 2014 |
| SSumM: Sparse Summarization of Massive Graphs K Lee, H Jo, J Ko, S Lim, K Shin ACM SIGKDD International Conference on Knowledge Discovery & Data Mining …, 2020 | 33 | 2020 |
| Modeling Multi-state Diffusion Process in Complex Networks: Theory and Applications Y Lin, JCS Lui, K Jung, S Lim Journal of Complex Networks 2 (4), 431-459, 2014 | 31 | 2014 |
| Differential Flattening: A Novel Framework for Community Detection in Multi-Layer Graphs J Kim, JG Lee, S Lim ACM Transactions on Intelligent Systems and Technology (TIST) 8 (2), 27, 2017 | 29 | 2017 |
| BlackHole: Robust Community Detection Inspired by Graph Drawing S Lim, J Kim, JG Lee IEEE International Conference on Data Engineering (ICDE), 25-36, 2016 | 25 | 2016 |
| TornadoAggregate: Accurate and Scalable Federated Learning via the Ring-Based Architecture J Lee, J Oh, S Lim, SY Yun, JG Lee AAAI Workshop (Towards Robust, Secure and Efficient Machine Learning), 2020 | 23 | 2020 |
| LinkBlackHole*: Robust Overlapping Community Detection Using Link Embedding J Kim, S Lim, JG Lee, BS Lee IEEE Transactions on Knowledge and Data Engineering (TKDE) 31 (11), 2138-2150, 2019 | 19 | 2019 |
| Stability of the Max-Weight Protocol in Adversarial Wireless Networks S Lim, K Jung, M Andrews IEEE/ACM Transactions on Networking (TON) 22 (6), 1859-1872, 2014 | 17 | 2014 |
| Stability of the Max-Weight Protocol in Adversarial Wireless Networks S Lim, K Jung, M Andrews IEEE Conference on Computer Communications (INFOCOM), 1251-1259, 2012 | 17 | 2012 |
| Analysis of Information Diffusion for Threshold Models on Arbitrary Networks S Lim, I Jung, S Lee, K Jung European Physical Journal B 88 (8), 201, 2015 | 13 | 2015 |
| Motif-Based Embedding for Graph Clustering S Lim, JG Lee Journal of Statistical Mechanics: Theory and Experiment 2016 (12), 123401, 2016 | 12 | 2016 |
| Phase Transitions for Information Diffusion in Random Clustered Networks S Lim, J Shin, N Kwak, K Jung European Physical Journal B 89 (9), 188, 2016 | 7 | 2016 |
| Graph Anomaly Detection with Graph Neural Networks: Current Status and Challenges H Kim, BS Lee, WY Shin, S Lim IEEE Access 10, 111820-111829, 2022 | 5 | 2022 |
| Phase Transition of Multi-state Diffusion Process in Networks S Lim, K Jung, JCS Lui ACM SIGMETRICS Performance Evaluation Review 41 (3), 31-33, 2013 | 5 | 2013 |
| Efficient spread-size approximation of opinion spreading in general social networks B Choe, Y Lin, S Lim, JCS Lui, K Jung Physical Review E 100 (5), 052311, 2019 | 3 | 2019 |
| OCSM: Finding Overlapping Cohesive Subgraphs with Minimum Degree J Kim, S Lim, J Kim Information Sciences 607, 585-602, 2022 | 2 | 2022 |
| SiReN: Sign-Aware Recommendation Using Graph Neural Networks C Seo, KJ Jeong, S Lim, WY Shin IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022 | 2 | 2022 |
| (p, n)-core: Core Decomposition in Signed Networks J Kim, S Lim International Conference on Database Systems for Advanced Applications …, 2022 | 2 | 2022 |
| Temporal Patternization of Power Signatures for Appliance Classification in NILM H Kim, S Lim Energies 14 (10), 2931, 2021 | 2 | 2021 |
| Cluster-aware Semantic Vector Learning using BERT in Natural Language Understanding S Jung, S Lim IEEE International Conference on Big Data and Smart Computing (BigComp), 91-98, 2021 | 2 | 2021 |
Kyomin JungProfessor, Department of Electrical and Computer Engineering, Seoul National University在 snu.ac.kr 的电子邮件经过验证
