| Slicenstitch: Continuous cp decomposition of sparse tensor streams T Kwon, I Park, D Lee, K Shin 2021 IEEE 37th International Conference on Data Engineering (ICDE), 816-827, 2021 | 12 | 2021 |
| Learning to pool in graph neural networks for extrapolation J Ko, T Kwon, K Shin, J Lee arXiv preprint arXiv:2106.06210, 2021 | 5 | 2021 |
| Begin: Extensive benchmark scenarios and an easy-to-use framework for graph continual learning J Ko, S Kang, T Kwon, H Moon, K Shin arXiv preprint arXiv:2211.14568, 2022 | 4 | 2022 |
| Neukron: Constant-size lossy compression of sparse reorderable matrices and tensors T Kwon, J Ko, J Jung, K Shin Proceedings of the ACM Web Conference 2023, 71-81, 2023 | 2 | 2023 |
| TensorCodec: Compact Lossy Compression of Tensors without Strong Data Assumptions T Kwon, J Ko, J Jung, K Shin 2023 IEEE International Conference on Data Mining (ICDM), 229-238, 2023 | | 2023 |
| Finding a Concise, Precise, and Exhaustive Set of Near Bi-Cliques in Dynamic Graphs H Shin, T Kwon, N Shah, K Shin Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022 | | 2022 |
| Continuous CP Decomposition of Sparse Tensor Streams T Kwon, I Park, D Lee, K Shin | | |
Kijung ShinAssociate Professor, KAISTVerified email at kaist.ac.kr
