| Understanding catastrophic overfitting in single-step adversarial training H Kim, W Lee, J Lee Proceedings of the AAAI Conference on Artificial Intelligence, 35(9), 2020 | 93 | 2020 |
| Patent network analysis and quadratic assignment procedures to identify the convergence of robot technologies WJ Lee, WK Lee, SY Sohn PloS one 11 (10), e0165091, 2016 | 59 | 2016 |
| Patent analysis to identify shale gas development in China and the United States WJ Lee, SY Sohn Energy policy 74, 111-115, 2014 | 43 | 2014 |
| Predicting bitcoin prices by using rolling window LSTM model J Huisu, J Lee, H Ko, W Lee Proceedings of the KDD data science in Fintech Workshop, London, UK, 19-23, 2018 | 26 | 2018 |
| Towards better understanding of training certifiably robust models against adversarial examples S Lee, W Lee, J Park, J Lee Advances in Neural Information Processing Systems 34, 953-964, 2021 | 22 | 2021 |
| Joint transfer of model knowledge and fairness over domains using wasserstein distance T Yoon, J Lee, W Lee IEEE Access 8, 123783-123798, 2020 | 18 | 2020 |
| Compact class-conditional domain invariant learning for multi-class domain adaptation W Lee, H Kim, J Lee Pattern Recognition 112, 107763, 2021 | 12 | 2021 |
| Fair clustering with fair correspondence distribution W Lee, H Ko, J Byun, T Yoon, J Lee Information Sciences 581, 155-178, 2021 | 10 | 2021 |
| Exploring the effect of multi-step ascent in sharpness-aware minimization H Kim, J Park, Y Choi, W Lee, J Lee arXiv preprint arXiv:2302.10181, 2023 | 7 | 2023 |
| Learning of indiscriminate distributions of document embeddings for domain adaptation S Park, W Lee, J Lee Intelligent Data Analysis 23 (4), 779-797, 2019 | 6 | 2019 |
| Information-based boundary equilibrium generative adversarial networks with interpretable representation learning J Hah, W Lee, J Lee, S Park Computational Intelligence and Neuroscience 2018, 2018 | 6 | 2018 |
| Bridged adversarial training H Kim, W Lee, S Lee, J Lee Neural Networks 167, 266-282, 2023 | 5 | 2023 |
| Parameter-free he-friendly logistic regression J Byun, W Lee, J Lee Advances in Neural Information Processing Systems 34, 8457-8468, 2021 | 5 | 2021 |
| Variational cycle-consistent imputation adversarial networks for general missing patterns W Lee, S Lee, J Byun, H Kim, J Lee Pattern Recognition 129, 108720, 2022 | 4 | 2022 |
| Instance weighting domain adaptation using distance kernel W Lee, J Lee, S Park Industrial Engineering & Management Systems 17 (2), 334-340, 2018 | 4 | 2018 |
| Loss landscape matters: Training certifiably robust models with favorable loss landscape S Lee, W Lee, J Park, J Lee | 2 | 2020 |
| Adjusted Impact Factor by using F min Search Algorithm W Lee, J Hah, N Kim Industrial Engineering & Management Systems 17 (1), 113-119, 2018 | 2 | 2018 |
| A Novel journal evaluation metric that adjusts the impact factors across different subject categories S Pyo, W Lee, J Lee Industrial Engineering and Management Systems 15 (1), 99-109, 2016 | 2 | 2016 |
| Fairness-Aware Multimodal Learning in Automatic Video Interview Assessment C Kim, J Choi, J Yoon, D Yoo, W Lee IEEE Access, 2023 | 1 | 2023 |
| Fast sharpness-aware training for periodic time series classification and forecasting J Park, H Kim, Y Choi, W Lee, J Lee Applied Soft Computing 144, 110467, 2023 | 1 | 2023 |
Jaewook LeeProfessor of Industrial Engineering, Seoul National Universitysnu.ac.kr의 이메일 확인됨
