+: equal contributions, *: corresponding authors, boldfaced: lab members

• Park, S. and Son, Y.* An Active Sampling Strategy for Minimax Fairness without Group Information, Submitted.

• Lee, S., Kim, H., Lee, W.*, and Son, Y.* Black-Box Adversarial Examples via Frequency Distortion against Fault Diagnosis Systems, Submitted.

• Lee, S., Choi, C., and Son, Y.* Deep Time-Series Clustering with Topological Information, Submitted.

• Lee, S., Choi, C., Do, H., and Son, Y.* BALT: Batch Active Learning for Time-Series Classification with Multi-Mode Exploration, Submitted.

• Choi, J.*, Son, Y.*, and Kang, J. Group-Exclusive Group Lasso in Deep Neural Networks: Application to Automatic Sensor Selection in Virtual Metrology, Submitted.

• Choi, J., Son, Y.*, and Jeong, M. K.* (2024+) Gaussian Kernel with Correlated Variables for Incomplete Data, Annals of Operations Research, Accepted.

• Lee, S., Choi, J., and Son, Y.* (2024+) Efficient Visibility Algorithm for High-frequency Time-series: Application to Fault Diagnosis with Graph Convolutional Network, Annals of Operations Research, Accepted.

• Akhyar, A., Zulkifley, M. A.*, Lee, J., Song, T., Han, J., Cho, C., Hyun, S., Son, Y., and Hong, B.-W. (2024) Deep artificial intelligence applications for natural disaster management systems: A methodological review, Ecological Indicators, 163, 112067.

• Lee, S., Lee, S., Lee, J., Lee, W.*, and Son, Y.* (2024) Graph Contrastive Learning with Consistency Regularization, Pattern Recognition Letters, 181, 43-49.

• Kim, H., Lee, S., Lee, J., Lee, W.*, and Son., Y.* (2024) Evaluating Practical Adversarial Robustness of Fault Diagnosis Systems via Spectrum-Aware Ensemble Method, Engineering Applications of Artificial Intelligence, 107980.

• Lee, S., Kim, W.*, and Son, Y.* (2024) Spatio-Temporal Consistency for Multivariate Time-Series Representation Learning, IEEE Access, 12, 30962-30975.

• Jeong, B., Lee, J., Lee., S., Lee., S. and Son, Y.*, and Kim, S. Y.* (2023) A 240 Fps In-column Binarized Neural Network Processing in CMOS Image Sensors, IEEE Transcations on Circuits and Systems II: Express Briefs, 70, 3907-3911.

• Lee, J.+, Lee, J.+, Shin, S., Son, Y.*, and Han, Y.* (2023) Machine Learning for the Expedited Screening of Hydrogen Evolution Catalysts for Transition Metal-Doped Transition Metal Dichalcogenides, International Journal of Energy Research, 2023, 6612054.

• Choi, E.+, Pang, K.+, Jeong, E., Lee, S., Son, Y.*, and Seo, M.-S.* (2023) Artificial intelligence in diagnosing dens evaginatus on periapical radiography with limited data availability, Scientific Reports, 13, 13232.

• Lee, J.+, Shin, S.+, Lee, J., Han, Y.-K.*, Lee, W.*, and Son, Y.* (2023) Genetic Descriptor Search Algorithm for Predicting Hydrogen Adsorption Free Energy of 2D Material, Scientific Reports, 13, 12729.

• Jeong, B., Lee, J., Choi, J., Song, M., Son, Y.*, and Kim, S. Y.* (2023) A 0.57 mW@1 FPS In-Column Analog CNN processor Integrated into CMOS Image Sensor, IEEE Access, 11, 61082-61090.

• Kim, W.+, Nam, K.+, and Son, Y.* (2023) Categorizing Affective Response of Customer with Novel Explainable Clustering Algorithm: The Case Study of Amazon Reviews, Electricl Commerce Research and Applications, 58, 101250.

• Lee, S.+, Park, H.+, Choi, C., Kim, W., Kim, K.K., Han, Y.-K., Kang, J., Kang. C.-J.*, and Son, Y.* (2023) Multi-order Graph Attention Network for Water Solubility Prediction and Interpretation, Scientific Reports, 13, 957.

• Son, Y. and Kim, W.* (2023) Development of Methodology for Classification of User Experience (UX) in Online Customer Review, Journal of Retailing and Customer Services, 71, 103210.

• Kakkar, B., Johri, P., Kumar, Y., Park, H., Son, Y., and Shaft, J.* (2022) An IoMT-based federated and deep transfer learning approach to the detection of diverse chest diseases using chest X-rays, Human-centric Computing and Information Sciences, 12, 24

• Choi, E., Lee, S., Jeong, E., Shin, S., Park, H., Youm, S., Son, Y.*, and Pang, K.* (2022) Artificial intelligence in positioning between mandibular third molar and inferior alveolar nerve on panoramic radiography, Scientific Reports, 12, 2456.

• Lee, S. and Son, Y.* (2022) Multitask Learning with Single Gradient Step Update for Task Balancing, Neurocomputing, 467, 442-453.

• Yu, H., Nam, K., Shin, S., Choi, M., Son, Y.*, and Chang, J.* (2021) Repetitive patterns in the locations of touch errors for two-thumb text entry on a smartphone, Applied Ergonomics, 97, 103541.

• Choi, J., Son, Y.*, and Jeong, M. K. (2021) Restricted Relevance Vector Machine for Missing Data and Application to Virtual Metrology, IEEE Transactions on Automation Science and Engineering, 19(4), 3172-3183.

• Lee, Y. and Son, Y.* (2021) Predicting Arbitrage-free American Option Prices Using Artificial Neural Network with Pseudo Inputs, Industrial Engineering & Management Systems, 20(2), 119-129.

• Lee, S. and Son, Y.* (2021) Motor Load Balancing with Roll Force Prediction for a Cold-Rolling Setup with Neural Networks, Mathematics, 9(12), 1367.

• Tavakkol, B.* and Son, Y. (2021) Fuzzy Kernel K-Medoids Clustering Algorithm for Uncertain Data Objects, Pattern Analysis and Applications, 24(3), 1287-1302.

• Yu, J. and Son, Y.*  (2021) Weighted Co-association Rate-based Laplacian Regularized Label Description for Semi-supervised Regression, Information Sciences, 545, 688-712. 

• Son, Y. and Kim, W.* (2020) Missing Value Imputation in Stature Estimation by Learning Algorithms Using Anthropometric Data: A Comparative Study, Applied Sciences, 10(14), 5020. 

• Choi, J., Lee, S., Son, Y.*, and Kim, S. Y.* (2020) Design of an Always-On Image Sensor Using an Analog Lightweight Convolutional Neural Network, Sensors, 20(11), 3101.

• Ijaz, M. F., Attique, M., and Son, Y.* (2020) Data-Driven Cervical Cancer Prediction Model with Outlier Detection and Over-Sampling Methods, Sensors, 20(10), 2809.

• Turkoz, M., Kim, S., Son, Y., Jeong, M. K.*, and Elsayed, E. A. (2020) Generalized support vector data description for anomaly detection, Pattern Recognition, 100, 107119.

• Lee, S., Lee, Y.-S., and Son, Y.* (2020) Forecasting Daily Temperatures with Different Time Interval Data Using Deep Neural Networks, Applied Sciences, 10(5), 1609. 

• Kim, C., Son, Y., and Youm, S.* (2019). Chronic Disease Prediction Using Character-Recurrent Neural Network in the Presence of Missing Information, Applied Sciences, 9(10), 2170. 

• Son, Y. and Kang, S.* (2018). Regression with re-labeling for noisy data, Expert Systems with Applications, 114, 578-587.

• Kim, Y., Son, Y., Kim, W.*, Jin, B., and Yun, M. H. (2018).  Classification of Children's Sitting Postures Using Machine Learning Algorithms, Applied Sciences, 8(8), 1280.

• Son, Y., Lee, S., Park, S., and Lee, J.* (2018). Representative Exemplars Using One-class Gaussian Process Regression, Pattern Recognition, 74, 185-197.

• Son, Y. and Lee, J.* (2016). Active Learning Using Transductive Sparse Bayesian Regression, Information Sciences, 374, 240-254.

• Kim, N., Son, Y., Lee, Y., and Lee, J.* (2016). Self-correcting ensemble using a latent consensus model, Applied Soft Computing, 47, 262-270.

• Son, Y., Byun, H., and Lee, J.* (2016). Nonparametric Machine Learning Models for Predicting the Credit Default Swaps: An Empirical Study, Expert Systems with Applications, 58, 210-220.

• Park, S., Lee, J., and Son, Y.* (2016). Predicting Market Impact Costs Using Nonparametric Machine Learning Models, PLoS ONE, 11(2), e0150243.

• Kim, K., Son, Y., and Lee, J.* (2015). Voronoi Cell-based Clustering Using a Kernel Support, IEEE Transactions on Knowledge and Data Engineering, 27(4), 1146-1156.

• Son, Y., Noh, D.-j., and Lee, J.* (2012). Forecasting trends of high-frequency KOSPI200 index data using learning classifiers, Expert Systems with Applications, 39(14), 11607-11615.