Selected Publications

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

2019.11.15 14:32

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Su-Jin Shin, Kyungwoo Song, and Il-Chul Moon, Hierarchically Clustered Representation Learning, AAI Conference on Artificial Intelligence (AAAI 2020). New York. Feb. 7-12 (Acceptance Rate : 20.6%)

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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 file
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 file
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 file
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 file
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 file
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) file
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) file
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 file
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). file
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). file
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) file
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 file
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 file
21 Joo, W., Lee, W., Park, S., & Moon, I. C. (2020). Dirichlet variational autoencoder. Pattern Recognition, Vol. 107, 107514. file
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 file
» 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 file
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 file
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 file
16 Kyungwoo Song, Mingi Ji, Sungrae Park, and Il-Chul Moon. Hierarchical Context enabled Recurrent Neural Network for Recommendation. AAAI Conference on Artificial Intelligence (AAAI 2019). Hawaii. Jan. 27-Feb. 1 file
15 Wonsung Lee, Sungrae Park, Weonyoung Joo, and Il-Chul Moon, Diagnosis Prediction via Medical Context Attention Networks Using Deep Generative Modeling, 2018 IEEE International Conference on Data Mining (ICDM'18), Nov. 17-20, Singapore (Short Paper) file
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