From technological development to social advance: A review of Industry 4.0 through machine learning C Lee, C Lim Technological Forecasting and Social Change 167, 120653, 2021 | 128 | 2021 |
Diet planning with machine learning: teacher-forced REINFORCE for composition compliance with nutrition enhancement C Lee, S Kim, C Lim, J Kim, Y Kim, M Jung Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 9 | 2021 |
Challenges of diet planning for children using artificial intelligence C Lee, S Kim, J Kim, C Lim, M Jung Nutrition Research and Practice 16 (6), 801, 2022 | 7 | 2022 |
MIND dataset for diet planning and dietary healthcare with machine learning: dataset creation using combinatorial optimization and controllable generation with domain experts C Lee, S Kim, S Jeong, C Lim, J Kim, Y Kim, M Jung Thirty-fifth Conference on Neural Information Processing Systems Datasets …, 2021 | 6 | 2021 |
Recommendation in Offline Stores: A Gamification Approach for Learning the Spatiotemporal Representation of Indoor Shopping J Shin, C Lee, C Lim, Y Shin, J Lim Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 3 | 2022 |
Human dietitians vs. Artificial intelligence: Which diet design do you prefer for your children? M Jung, C Lim, C Lee, S Kim, J Kim Journal of Allergy and Clinical Immunology 147 (2), AB117, 2021 | 2 | 2021 |
Toward a context-aware serendipitous recommendation system C Lee, G Lee, C Lim Advances in Service Science: Proceedings of the 2018 INFORMS International …, 2019 | 1 | 2019 |
Reward Dropout Improves Control: Bi-objective Perspective on Reinforced LM C Lee, C Lim arXiv e-prints, arXiv: 2310.04483, 2023 | | 2023 |