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36 |
DongHyeok Shin, Seungjae Shin, Il-Chul Moon, Frequency Domain-based Dataset Distillation, Neural Information Processing Systems (NeurIPS 2023), New Orleans, USA, Dec 10-Dec 16, 2023
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35 |
Suhyeon Jo, Donghyeok Shin, Byeonghu Na, JoonHo Jang, and Il-Chul Moon, Hierarchical Multi-Label Classification with Partial Labels and Unknown Hierarchy, ACM International Conference on Information and Knowledge Management (CIKM 2023)
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34 |
Yoon-Yeong Kim, Youngjae Cho, JoonHo Jang, Byeonghu Na, Yeongmin Kim, Kyungwoo Song, Wanmo Kang, Il-Chul Moon, SAAL: Sharpness-Aware Active Learning, International Conference on Machine Learning (ICML 2023), Hawaii, USA, Jul 25-27, 2023
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33 |
Dongjun Kim, Yeongmin Kim, Se Jung Kwon, Wanmo Kang, Il-Chul Moon, Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models, International Conference on Machine Learning (ICML 2023), Hawaii, USA, Jul 25-27, 2023
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32 |
Seungjae Shin, Heesun Bae, DongHyeok Shin, Weonyoung Joo, Il-Chul Moon, Loss Curvature Matching for Dataset Selection and Condensation, International Conference on Artificial Intelligence and Statistics (AISTATS 23), Valencia, Spain, Apr 25-27, 2023
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31 |
Dongjun Kim, Byeonghu Na, Se Jung Kwon, Dongsoo Lee, Wanmo Kang, Il-Chul Moon, Maximum Likelihood Training of Implicit Nonlinear Diffusion Model, Neural Information Processing Systems (NeurIPS 2022), New Orleans, USA, Nov 28-Dec 9, 2022
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30 |
JoonHo Jang, Byeonghu Na, Dong Hyeok Shin, Mingi Ji, Kyungwoo Song, Il-Chul Moon, Unknown-Aware Domain Adversarial Learning for Open-Set Domain Adaptation, Neural Information Processing Systems (NeurIPS 2022), New Orleans, USA, Nov 28-Dec 9, 2022
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29 |
Dongjun Kim, Seungjae Shin, Kyungwoo Song, Wanmo Kang, Il-Chul Moon, Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation, International Conference on Machine Learning (ICML 2022)
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28 |
HeeSun Bae, Seungjae Shin, Byeonghu Na, JoonHo Jang, Kyungwoo Song, Il-Chul Moon, From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model, International Conference on Machine Learning (ICML 2022)
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27 |
Yooon-Yeong Kim, Kyungwoo Song, JoonHo Jang, Il-chul Moon, LADA: Look-Ahead Data Acquisition via Augmentation for Deep Active Learning, Neural Information Processing Systems (NeurIPS 2021), Virtual, Dec. 7-10, 2021
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26 |
Kim, D., Yun, TS., Moon, IC. et al. Automatic calibration of dynamic and heterogeneous parameters in agent-based models. Auton Agent Multi-Agent Syst 35, 46 (2021).
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25 |
Mingi Ji, Seungjae Shin, Seunghyun Hwang, Gibeom Park, Il-Chul Moon. Refine Myself by Teaching Myself : Feature Refinement via Self-Knowledge Distillation. Conference on Computer Vision and Pattern Recognition (CVPR 2021).
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24 |
Hyemi Kim, Seungjae Shin, JoonHo Jang, Kyungwoo Song, Weonyoung Joo, Wanmo Kang, and Il-Chul Moon, Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder, AAAI Conference on Artificial Intelligence (AAAI 2021)
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23 |
Kyungwoo Song, Yohan Jung, Dongjun Kim, and Il-Chul Moon, Implicit Kernel Attention, AAAI Conference on Artificial Intelligence (AAAI 2021), Virtual Conference, Feb. 2-9
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22 |
Byeonghu Na, Hyemi Kim, Kyungwoo Song, Weonyoung Joo, Yoon-Yeong Kim, and Il-Chul Moon, Deep Generative Positive-Unlabeled Learning under Selection Bias, ACM International Conference on Information and Knowledge Management (CIKM 2020), 2020, Oct. 19
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21 |
Joo, W., Lee, W., Park, S., & Moon, I. C. (2020). Dirichlet variational autoencoder. Pattern Recognition, Vol. 107, 107514.
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20 |
Mingi Ji, Weonyoung Joo, Kyungwoo Song, Yoon-Yeong Kim, and Il-Chul Moon, Sequential Recommendation with Relation-Aware Kernelized Self-Attention. AAAI Conference on Artificial Intelligence (AAAI 2020). New York. Feb. 7-12
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19 |
Su-Jin Shin, Kyungwoo Song, and Il-Chul Moon, Hierarchically Clustered Representation Learning, AAAI Conference on Artificial Intelligence (AAAI 2020). New York. Feb. 7-12
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18 |
Kyungwoo Song, JoonHo Jang, Seung jae Shin and Il-Chul Moon, Bivariate Beta-LSTM. AAAI Conference on Artificial Intelligence (AAAI 2020). New York. Feb. 7-12
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17 |
Sungrae Park, Kyungwoo Song, Mingi Ji, Wonsung Lee, and Il-Chul Moon, Adversarial Dropout for Recurrent Neural Networks. AAAI Conference on Artificial Intelligence (AAAI 2019). Hawaii. Jan. 27-Feb. 1
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