Information-Based Boundary Equilibrium Generative Adversarial Networks with Interpretable Representation Learning. - Junghoon Hah; Woojin Lee; Jaewook Lee 001; Saerom Park (Comput. Intell. Neurosci., 2018)

Learning representative exemplars using one-class Gaussian process regression. - Youngdoo Son; Sujee Lee; Saerom Park; Jaewook Lee 001 (Pattern Recognit., 2018)

Security-preserving Support Vector Machine with Fully Homomorphic Encryption. - Saerom Park; Jaewook Lee 001; Jung Hee Cheon; Juhee Lee; Jaeyun Kim; Junyoung Byun (SafeAI@AAAI, 2019)

Learning of indiscriminate distributions of document embeddings for domain adaptation. - Saerom Park; Woojin Lee; Jaewook Lee 001 (Intell. Data Anal., 2019)

Semi-supervised distributed representations of documents for sentiment analysis. - Saerom Park; Jaewook Lee 001; Kyoungok Kim (Neural Networks, 2019)

Lipschitz-Certifiable Training with a Tight Outer Bound. - Sungyoon Lee; Jaewook Lee 001; Saerom Park (NeurIPS, 2020)

HE-Friendly Algorithm for Privacy-Preserving SVM Training. - Saerom Park; Junyoung Byun; Joohee Lee; Jung Hee Cheon; Jaewook Lee 001 (IEEE Access, 2020)

Stability Analysis of Denoising Autoencoders Based on Dynamical Projection System. - Saerom Park; Jaewook Lee 001 (IEEE Trans. Knowl. Data Eng., 2021)

Privacy-Preserving Fair Learning of Support Vector Machine with Homomorphic Encryption. - Saerom Park; Junyoung Byun; Joohee Lee (WWW, 2022)

Fairness Audit of Machine Learning Models with Confidential Computing. - Saerom Park; Seongmin Kim; Yeon-sup Lim (WWW, 2022)

Efficient Generation of Program Execution Hash. - Eunyeong Ahn; Sunjin Kim; Saerom Park; Jong-Uk Hou; Daehee Jang (IEEE Access, 2022)

Efficient differentially private kernel support vector classifier for multi-class classification. - Jinseong Park 001; Yujin Choi; Junyoung Byun; Jaewook Lee 001; Saerom Park (Inf. Sci., 2023)

Efficient homomorphic encryption framework for privacy-preserving regression. - Junyoung Byun; Saerom Park; Yujin Choi; Jaewook Lee 001 (Appl. Intell., 2023)

Fair Sampling in Diffusion Models through Switching Mechanism. - Yujin Choi; Jinseong Park 001; Hoki Kim; Jaewook Lee 001; Saerom Park (AAAI, 2024)

Efficient Privacy-Preserving Counting Method with Homomorphic Encryption. - Jae-yun Kim; Jieun Yun; Jung Hee Cheon; Saerom Park (ICISC, 2024)

Privacy-Preserving Embedding via Look-up Table Evaluation with Fully Homomorphic Encryption. - Jaeyun Kim; Saerom Park; Joohee Lee; Jung Hee Cheon (ICML, 2024)

The SaTML '24 CNN Interpretability Competition: New Innovations for Concept-Level Interpretability. - Stephen Casper; Jieun Yun; Joonhyuk Baek; Yeseong Jung; Minhwan Kim; Kiwan Kwon; Saerom Park; Hayden Moore; David Shriver; Marissa Connor; Keltin Grimes; Angus Nicolson; et al. (CoRR, 2024)

Privacy-preserving inference resistant to model extraction attacks. - Junyoung Byun; Yujin Choi; Jaewook Lee 001; Saerom Park (Expert Syst. Appl., 2024)

Verifiable computation over encrypted data via MPC-in-the-head zero-knowledge proofs. - Joohee Lee; Sangrae Cho; Soohyung Kim; Saerom Park (Int. J. Inf. Sec., 2025)

Unlearning's Blind Spots: Over-Unlearning and Prototypical Relearning Attack. - SeungBum Ha; Saerom Park; Sung Whan Yoon (CoRR, 2025)