| SSumM: Sparse Summarization of Massive Graphs K Lee, H Jo, J Ko, S Lim, K Shin Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 52 | 2020 |
| Effective training strategies for deep-learning-based precipitation nowcasting and estimation J Ko, K Lee, H Hwang, SG Oh, SW Son, K Shin Computers & Geosciences 161, 105072, 2022 | 24 | 2022 |
| Dpgs: Degree-preserving graph summarization H Zhou, S Liu, K Lee, K Shin, H Shen, X Cheng Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021 | 21 | 2021 |
| Monstor: an inductive approach for estimating and maximizing influence over unseen networks J Ko, K Lee, K Shin, N Park 2020 IEEE/ACM International Conference on Advances in Social Networks …, 2020 | 15* | 2020 |
| Personalized graph summarization: formulation, scalable algorithms, and applications S Kang, K Lee, K Shin 2022 IEEE 38th International Conference on Data Engineering (ICDE), 2319-2332, 2022 | 12 | 2022 |
| Slugger: Lossless hierarchical summarization of massive graphs K Lee, J Ko, K Shin 2022 IEEE 38th International Conference on Data Engineering (ICDE), 472-484, 2022 | 9 | 2022 |
| Deep-learning-based precipitation nowcasting with ground weather station data and radar data J Ko, K Lee, H Hwang, K Shin 2022 IEEE International Conference on Data Mining Workshops (ICDMW), 1063-1070, 2022 | 4 | 2022 |
| Are edge weights in summary graphs useful?-a comparative study S Kang, K Lee, K Shin Pacific-Asia Conference on Knowledge Discovery and Data Mining, 54-67, 2022 | 3 | 2022 |
Kijung ShinAssociate Professor, KAIST在 kaist.ac.kr 的电子邮件经过验证
