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Jaemin Yoo
Jaemin Yoo
Assistant Professor, KAIST
Verified email at kaist.ac.kr - Homepage
Title
Cited by
Cited by
Year
Accurate Multivariate Stock Movement Prediction via Data-Axis Transformer with Multi-Level Contexts
J Yoo, Y Soun, Y Park, U Kang
ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), 2037-2045, 2021
1212021
Knowledge Extraction with No Observable Data
J Yoo, M Cho, T Kim, U Kang
Advances in Neural Information Processing Systems (NeurIPS), 2701-2710, 2019
1182019
Efficient learning of bounded-treewidth Bayesian networks from complete and incomplete data sets
M Scanagatta, G Corani, M Zaffalon, J Yoo, U Kang
International Journal of Approximate Reasoning 95, 152-166, 2018
422018
Accurate stock movement prediction with self-supervised learning from sparse noisy tweets
Y Soun, J Yoo, M Cho, J Jeon, U Kang
2022 IEEE International Conference on Big Data (Big Data), 1691-1700, 2022
412022
Towards deep attention in graph neural networks: Problems and remedies
SY Lee, F Bu, J Yoo, K Shin
International Conference on Machine Learning, 18774-18795, 2023
302023
Model-agnostic augmentation for accurate graph classification
J Yoo, S Shim, U Kang
Proceedings of the ACM Web Conference 2022, 1281-1291, 2022
282022
Midas: Representative sampling from real-world hypergraphs
M Choe, J Yoo, G Lee, W Baek, U Kang, K Shin
Proceedings of the ACM Web Conference 2022, 1080-1092, 2022
262022
Attention-Based Autoregression for Accurate and Efficient Multivariate Time Series Forecasting
J Yoo, U Kang
SIAM International Conference on Data Mining (SDM), 531-539, 2021
222021
Signed graph diffusion network
J Jung, J Yoo, U Kang
arXiv preprint arXiv:2012.14191, 2020
222020
Supervised Belief Propagation: Scalable Supervised Inference on Attributed Networks
J Yoo, S Jo, U Kang
IEEE International Conference on Data Mining (ICDM), 595-604, 2017
212017
Belief Propagation Network for Hard Inductive Semi-Supervised Learning
J Yoo, H Jeon, U Kang
International Joint Conference on Artificial Intelligence (IJCAI), 4178-4184, 2019
192019
Fast and scalable distributed loopy belief propagation on real-world graphs
S Jo, J Yoo, U Kang
ACM International Conference on Web Search and Data Mining (WSDM), 297-305, 2018
182018
Accurate node feature estimation with structured variational graph autoencoder
J Yoo, H Jeon, J Jung, U Kang
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
162022
Accurate Graph-Based PU Learning without Class Prior
J Yoo, J Kim, H Yoon, G Kim, C Jang, U Kang
IEEE International Conference on Data Mining (ICDM), 827-836, 2021
162021
Reciprocity in directed hypergraphs: measures, findings, and generators
S Kim, M Choe, J Yoo, K Shin
Data Mining and Knowledge Discovery 37 (6), 2330-2388, 2023
152023
Sampling Subgraphs with Guaranteed Treewidth for Accurate and Efficient Graphical Inference
J Yoo, U Kang, M Scanagatta, G Corani, M Zaffalon
ACM International Conference on Web Search and Data Mining (WSDM), 708-716, 2020
142020
Less is more: Slimg for accurate, robust, and interpretable graph mining
J Yoo, MC Lee, S Shekhar, C Faloutsos
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
9*2023
Classification of edge-dependent labels of nodes in hypergraphs
M Choe, S Kim, J Yoo, K Shin
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
92023
How Transitive Are Real-World Group Interactions?-Measurement and Reproduction
S Kim, F Bu, M Choe, J Yoo, K Shin
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
92023
Mining of real-world hypergraphs: Patterns, tools, and generators
G Lee, J Yoo, K Shin
Proceedings of the 31st ACM International Conference on Information …, 2022
92022
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