| Lipschitz-certifiable training with a tight outer bound S Lee, J Lee, S Park Advances in Neural Information Processing Systems 33, 16891-16902, 2020 | 42 | 2020 |
| HE-friendly algorithm for privacy-preserving SVM training S Park, J Byun, J Lee, JH Cheon, J Lee IEEE Access 8, 57414-57425, 2020 | 37 | 2020 |
| Semi-supervised distributed representations of documents for sentiment analysis S Park, J Lee, K Kim Neural Networks 119, 139-150, 2019 | 22 | 2019 |
| Predicting market impact costs using nonparametric machine learning models S Park, J Lee, Y Son PLoS One 11 (2), e0150243, 2016 | 21 | 2016 |
| Privacy-preserving fair learning of support vector machine with homomorphic encryption S Park, J Byun, J Lee Proceedings of the ACM Web Conference 2022, 3572-3583, 2022 | 12 | 2022 |
| Security-preserving Support Vector Machine with Fully Homomorphic Encryption. S Park, J Lee, JH Cheon, J Lee, J Kim, J Byun SafeAI@ AAAI 2301, 2019 | 12 | 2019 |
| Fairness Audit of Machine Learning Models with Confidential Computing S Park, S Kim, Y Lim Proceedings of the ACM Web Conference 2022, 3488-3499, 2022 | 11 | 2022 |
| Learning representative exemplars using one-class Gaussian process regression Y Son, S Lee, S Park, J Lee Pattern Recognition 74, 185-197, 2018 | 8 | 2018 |
| Efficient differentially private kernel support vector classifier for multi-class classification J Park, Y Choi, J Byun, J Lee, S Park Information Sciences 619, 889-907, 2023 | 7 | 2023 |
| 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 | 7 | 2018 |
| Privacy‐preserving evaluation for support vector clustering J Byun, J Lee, S Park Electronics Letters 57 (2), 61-64, 2021 | 5 | 2021 |
| Learning of indiscriminate distributions of document embeddings for domain adaptation S Park, W Lee, J Lee Intelligent Data Analysis 23 (4), 779-797, 2019 | 5 | 2019 |
| Defensive denoising methods against adversarial attack S Lee, J Lee | 5 | 2018 |
| Inductive ensemble clustering using kernel support matching S Park, J Hah, J Lee Electronics Letters 53 (25), 1625-1626, 2017 | 5 | 2017 |
| Efficient homomorphic encryption framework for privacy-preserving regression J Byun, S Park, Y Choi, J Lee Applied Intelligence 53 (9), 10114-10129, 2023 | 3 | 2023 |
| Instance weighting domain adaptation using distance kernel W Lee, J Lee, S Park Industrial Engineering & Management Systems 17 (2), 334-340, 2018 | 3 | 2018 |
| Stability Analysis of Denoising Autoencoders Based on Dynamical Projection System S Park, J Lee IEEE Transactions on Knowledge and Data Engineering 33 (8), 3155-3159, 2020 | 2 | 2020 |
| Efficient Generation of Program Execution Hash E Ahn, S Kim, S Park, JU Hou, D Jang IEEE Access 10, 61707-61720, 2022 | | 2022 |
| Density-based Representation Learning with Applications to Sentiment Analysis and Domain Adaptation S Park | | 2018 |
| Semi-supervised Document Embedding Adjusting Local Structure for Sentiment Analysis HJ Saerom Park, Jaewook Lee, Kyoungok Kim the WiML 2016 Workshop joint with NIPS 2016, 0 | | |
Jaewook LeeProfessor of Industrial Engineering, Seoul National UniversityVerified email at snu.ac.kr
