Il-Chul Moon
Il-Chul Moon
Associate Professor, Department of Industrial and Systems Engineering, KAIST
Verified email at - Homepage
Cited by
Cited by
Adversarial dropout for supervised and semi-supervised learning
S Park, JK Park, SJ Shin, IC Moon
Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018
Mining social networks for personalized email prioritization
S Yoo, Y Yang, F Lin, IC Moon
Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009
Analysis of twitter lists as a potential source for discovering latent characteristics of users
D Kim, Y Jo, IC Moon, A Oh
ACM CHI workshop on microblogging 6, 2010
Modeling and simulating terrorist networks in social and geospatial dimensions
IC Moon, KM Carley
IEEE Intelligent Systems 22 (5), 40-49, 2007
Refine myself by teaching myself: Feature refinement via self-knowledge distillation
M Ji, S Shin, S Hwang, G Park, IC Moon
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021
Dirichlet variational autoencoder
W Joo, W Lee, S Park, IC Moon
Pattern Recognition 107, 107514, 2020
Efficient extraction of domain specific sentiment lexicon with active learning
S Park, W Lee, IC Moon
Pattern Recognition Letters 56, 38-44, 2015
ORA User's Guide 2008
KM Carley, D Columbus, M DeReno, J Reminga, I Moon
Institute for Software Research, School of Computer Science. Pittsburgh …, 2009
Augmented variational autoencoders for collaborative filtering with auxiliary information
W Lee, K Song, IC Moon
Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017
Refining generative process with discriminator guidance in score-based diffusion models
D Kim, Y Kim, SJ Kwon, W Kang, IC Moon
arXiv preprint arXiv:2211.17091, 2022
Soft truncation: A universal training technique of score-based diffusion model for high precision score estimation
D Kim, S Shin, K Song, W Kang, IC Moon
arXiv preprint arXiv:2106.05527, 2021
Counterfactual fairness with disentangled causal effect variational autoencoder
H Kim, S Shin, JH Jang, K Song, W Joo, W Kang, IC Moon
Proceedings of the AAAI Conference on Artificial Intelligence 35 (9), 8128-8136, 2021
Diagnosis prediction via medical context attention networks using deep generative modeling
W Lee, S Park, W Joo, IC Moon
2018 IEEE International Conference on Data Mining (ICDM), 1104-1109, 2018
Are we treating networks seriously? The growth of network research in public administration & public policy
S Hwang, IC Moon
Connections 29 (2), 4-17, 2009
Maximum likelihood training of implicit nonlinear diffusion model
D Kim, B Na, SJ Kwon, D Lee, W Kang, I Moon
Advances in Neural Information Processing Systems 35, 32270-32284, 2022
Lada: Look-ahead data acquisition via augmentation for deep active learning
YY Kim, K Song, JH Jang, IC Moon
Advances in Neural Information Processing Systems 34, 22919-22930, 2021
Personalized email prioritization based on content and social network analysis
Y Yang, S Yoo, F Lin, IC Moon
IEEE Intelligent Systems 25 (04), 12-18, 2010
Hierarchical context enabled recurrent neural network for recommendation
K Song, M Ji, S Park, IC Moon
Proceedings of the AAAI conference on artificial intelligence 33 (01), 4983-4991, 2019
Sequential recommendation with relation-aware kernelized self-attention
M Ji, W Joo, K Song, YY Kim, IC Moon
Proceedings of the AAAI conference on artificial intelligence 34 (04), 4304-4311, 2020
Identifying prescription patterns with a topic model of diseases and medications
S Park, D Choi, M Kim, W Cha, C Kim, IC Moon
Journal of biomedical informatics 75, 35-47, 2017
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