Dongha Kim, Yongchan Choi, Kunwoong Kim, Ilsang Ohn and Yongdai Kim. (2024) IOFM: Using the Interpolation Technique on the Over-Fitted Models to Identify Clean-Annotated Samples. Accpeted by AAAI.

  Ilsang Ohn, Lizhen Lin and Yongdai Kim (2023). A Bayesian sparse factor model with adaptive posterior concentration. Accepted by Bayesian Ananlysis.

  Gwangsoo Kim, Changdong Yoo and Yongdai Kim (2023) Bayesian analysis of the generalized additive proportional hazards model: Asymptotic studies. Accepted by Bayesian Ananlysis.

  Dongyoon Yang, Insung Kong and Yongdai Kim (2023). Enhancing Adversarial Robustness in Low-Label Regime via Adaptively Weighted Regularization and Knowledge Distillation. Accepted by ICCV.

  Jaesung Hwang, Joongho Won and Yongdai Kim (2023). Characterization of the solution set of the generalized Lasso problems for non-full rank cases. Accepted by Electrical Journal of Statistics.

  Insung Kong, Yuha Park, Joonhyuk Jung, Kwonsang Lee, Yongdai Kim (2023). Covariate balancing using the integral probability metric for causal inference. Accepted by ICML2023.

  Insung Kong, Dongyoon Yang, Jongjin Lee, Ilsang Ohn, GYUSEUNG BAEK, Yongdai Kim (2023). Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference. Accepted by ICML2023.

  Dongyoon Yang, Insung Kong, Yongdai Kim (2023). Improving adversarial robustness by putting more regularizations on less robust samples. Accepted by ICML2023.

  Seonghyeon Kim, Sara Kim, Kunwoong Kim and Yongdai Kim (2023). Lq regularization for fair AI robust to covariate shift. Accepted by Statistical Analysis and Data Mining.

  Minwoo Chae, Dongha Kim, Yongdai Kim and Lizhen Lin (2023). A likelihood approach to nonparametric estimation of a singular distribution using deep generative models. Accepted by Journal of Machine Learning Research.

  June Young Chun, Hwichang Jeong and Yongdai Kim (2022). Identifying susceptibility of children and adolescents to the omicron variants. Accepted by BMC Medicine.

  Sukhyun Ryu et al. (2022). Epidemiology and transmission dynamics of infectious diseases and control measures. Accepted by Viruses.

  HeyIn Lee et al. (2022). Evaluation of Optimal Assessment Schedules for Surveillance After Definitive Locoregional Treatment of Locally Advanced Head and Neck Cancer: A Retrospective Cohort Study With Parametric Modeling of Event-Free Survival. Accpeted by JAMA Otolaryngology–Head & Neck Surgery

  Kuhwan Jeong, Minwoo Chae and Yongdai Kim (2022). Online Learning for the Dirichlet Process Mixture Model via Weakly Conjugate Approximation. Accepted by CSDA.

  Kunwoong Kim, Ilsang Ohn, Sara Kim and Yongdai Kim (2022) SLIDE: a surrogate fairness constraint to ensure fairness consistency. Accepted by Neural Networks.

  Dongha Kim, Kunwoong Kim, Insung Kong, Ilsang Ohn & Yongdai Kim (2022) Learning fair representation with a parametric integral probability. Accepted by ICML

  June Young Chun, Hwichang Jeong and Yongdai Kim (2022) Age-Varying Susceptibility to the Delta Variant (B.1.617.2) of SARS-CoV-2, JAMA-Network Open.

  Kim, W., Kim, S., Na, M. H., & Kim, Y. (2022) A modified least angle regression algorithm for interaction selection with heredity. Accepted by Statistical Analysis and Data Mining.

  Yongdai Kim and Hwichang Jeong (2022). Learning fair prediction models with an imputed sensitive variable: Empirical studies. Accepted by CSAM.

  Rafael Weißbach et al. (2021). Left-censored dementia incidences in estimating cohort effects. Accepted by Lifetime Data Analysis.

  Ho Kang et al. (2021). Radiological assessment schedule for 1p/19q-codeleted gliomas during the surveillance period using parametric modeling. Accepted by Neuro-Oncol Adv.

  June Young Chun, Hwichang Jeong and Yongdai Kim (2021) Contact-adjusted immunity levels against SARS-CoV-2 in Korea and Prospects for Achieving herd immunity. Journal of Korean Medical Science.

  Ilsang Ohn and Yongdai Kim (2021) Nonconvex Sparse Regularization for Deep Neural Networks and its Optimality. Neural Computation. 1-42.

  Kuwhan Jung and Yongdai Kim (2021) Dynamic Hierarchical Dirichlet Processes Topic Model using the Power Prior approach. Journal of Korean Statsitical Society. 50, 860-873.

  Ilsang Ohn and Yongdai Kim (2021) Posterior consistency of factor dimensionality in high-dimensional sparse factor models. Accpted by Bayesian Analysis.

  Yongdai Kim, Ilsang Ohn and Dongha Kim (2021) Fast convergence rates of deep neural networks for classification. Neural Networks, 138, 179-197.

  Dongha Kim and Yongdai Kim (2021) Understanding effects of architecture design to invariance and complexity in deep neural network. Accpeted by IEEE Access.

  Kim, Minjin, Kim, Yongdai, Kim, Dongha and Paik Cho, Myunghee (2021) Kernel-convoluted Deep Neural Networks with Data Augmentatio. The 35th AAAI.

  So Young Ji, et al. (2020). Radiological assessment schedule for high-grade glioma patients after standard treatment. Accepted by Neuro-Oncology.

  Kim Dongha, Jaesung Hwang and Yongdai Kim (2020). On casting importance weighted auto-encoder to an EM algorithm to learn deep generative models. AISTAT 2020, Italy.

  Weissbach, R., Kim, Y., Dorre, A., Fink, A. and Doblhammer, G. (2020). Left-censroed dementia incidences in estimating cohort effect. Accepted by Lifetime Data Analysis.

  Jeon, JJ et al. (2020). Learning Multiple Quantiles with Neural Networks. Accepted by JCGS.

  June Young Chun, Gyuseung Baek and Yongdai Kim (2020). Transmission onset distribution of COVID-19. Accepted by International Journal of Infectious disease.

  Jeon, Jong-June, Kim, Yongdai, Won, Sungho and Choi, Hosik. (2020). Primal path algorithm for compositional data analysis. Accepted by CSDA.

  Ohn, Ilsang et al. (2020) Bayesian uncertainty decomposition for hydrological projection, Journal of the Korean Statistical Society, 49(3), 953-975.

  Lee, Young Hoon, Kim, Yongdai and Kim, Sara (2019). Competitive balance with unbalanced schedules. Journal of Quantitative Analysis in Sports. 15(3), 239-260.

  Kim, D., Woo, J., Shin, J., Lee, J. and Kim, Y. (2019). Can search engine data improve accuracy of demand forecasting for new products? Evidence from automotive market. Industrial Management & Data Systems. 119(5), 1089-1103.

  Ilsang Ohn and Yongdai Kim (2019). Smooth function approximation by deep neural networks with general activation functions. Entropy. 21(7), 627.

  Yongdai Kim, Ilsang Ohn, Jae-Kyung Lee and Young-Oh Kim (2019). Generalizing uncertainty decomposition theory in climate change impact assessments. Journal of Hydrology X. 3, 100024.

  Frank, Gordon, Chae, Minwoo and Kim, Yongdai (2019) Additive Time-Dependent Hazard Model with Doubly Truncated Data. Journal of the Korean Statistical Society. 48(2), 179-193.

  Lee, Young Hoon, Kim, Yongdai and Kim, Sara (2019). A Bias-Corrected Estimator of Competitive Balance in Sports Leagues. Journal of Sports Economics. 20(4), 479-508.

  Chae, Minwoo, Kim, Yongdai and Kleijin, Bas (2019). The semi-parametric Bernstein-von Mises theorem for regression models with symmetric errors. Statistica Sinica. 29, 1465-1487.

  Yongdai Kim, Ilsang Ohn and Dongha Kim (2018). Fast convergence rates of deep neural networks for classification, Accepted by Neural Networks.

  Jung Hee Chun, Duhyeong Kim, Yongdai Kim and Yongsoo Song (2018). Ensemble method for privacy-preserving logistic regression based on homomorphic encryption. IEEE Access. 6, 46938–46948.

  Jungyeon Kim, Yohan Lim, Yongdai Kim and Woncheol Jang (2018) Bayesian variable selection with heredity constraints. JKSS. 47(3), 314-329.

  Hosik Choi, Yongdai Kim, Sunghoon Kwon and Changyi Park (2017). A robust support vector machine for labelling errors. Communications in Statistics – Simulation and Computation. 46(8), 6061-6073.

  Gwangsu Kim,, Chao–Qiang Lai, Donna K. Arnett, Laurence D. Parnell,, Jose M. Ordovas, Yongdai Kim, Joungyoun Kim (2017). Detection of Gene–Environment Interactions in a Family–Based Population Using SCAD, Statistics in Medicine. 36(22), 3547-3559.

  Sun Mi Kim, Yongdai Kim, Kuhwan Jeong, Heeyeong Jeong, Jiyoung Kim (2017). Logistic lasso regression for the diagnosis of breast cancer using clinical demographic data and the BI-RADS lexicon for ultrasonography. Ultrasonography. Publised online.

  Lim, Hwa Kyung, Kim, Yongdai and Kim, Min-Kyoon (2017). Failure prediction using sequential pattern mining in the wire bonding process, IEEE Transactions on Semiconductor Manufacturing. 30, 285–292.

  Kwon, S., Ahn, J., Jang, W., Lee, S., & Kim, Y. (2017). A doubly sparse approach for group variable selection. Annals of the Institute of Statistical Mathematics, 1-29. 69, 997-1025.

  Gwangsu Kim, Yongdai Kim and Taeryon Choi (2017). Bayesian analysis of the proportional hazards model with time-varying coefficients. Scandinavian Journal of Statistics. 44, 524-544.

  Jae-Kyeong Lee, Young-Oh Kim and Yongdai Kim (2017). A new uncertainty analysis in the climate change impact assessment. International Journal of Climatology. 37, 3837–3846.

  Ho Il Yoon, Oh-Ran Kwon, Kyung Nam Kang, Yong Sung Shin, Ho Sang Shin, Eun Hee Yeon, Keon Young Kwon, Ilseon Hwang, Yun Kyung Jeon, Yongdai Kim, Chul Woo Kim. (2016). Diagnostic value of combining tumor and inflammatory markers in lung cancer. Journal of Cancer Prevention, 21, 187-193.

  Yongdai Kim, Guwhan Jung, Byungyup Kan and Hyjoo Jung (2016). An Online Gibbs Sampler Algorithm for Hierarchical Dirichlet Processes Prior. Proceeding at ECML-PKDD.

  Kim, Y. I., Ahn, J. M., Sung, H. J., Na, S. S., Hwang, J., Kim, Y., & Cho, J. Y. (2016). Meta-markers for the differential diagnosis of lung cancer and lung disease. Journal of proteomics, 148, 36-43.

  Sangin Lee, Sunghoon Kwon and Yongdai Kim (2016). A modified local quadratic approximation algorithm for penalized optimization problems. Computational Statistics and Data Analysis. 94, 275-286.

  Kim, Y., & Jeon, J. J. (2016). Consistent model selection criteria for quadratically supported risks. The Annals of Statistics, 44(6), 2467-2496.

  Woo, S. E., Chae, M., Jebb, A. T., & Kim, Y. (2016). A Closer Look at the Personality-Turnover Relationship: Criterion Expansion, Dark Traits, and Time. Journal of Management, 42(2), 357-385.

  Heng Lian and Yongdai Kim. (2016) Nonconvex penalized reduced rank regression and its oracle properties. Journal of Multivariate Analysis. 143, 383-393.

  Sangin Lee, Miae Oh and Yongdai Kim (2016) Sparse optimization for nonconvex group penalized estimation, Journal of Statistical Computation and Simulation. 86(3), 597-610.

  Yongdai Kim, Ilsang On and Young-Oh Kim. (2015). Scaled ridge estimator and its application to multimodel ensemble approaches for climate prediction. Journal of Korean Statistical Society. 45, 307-313.

  Yongdai Kim, Jong-Jun Jeon, Sangmi Han, (2015). A necessary condition for the oracle property. Scandinavian Journal of Statistics, 43, 610-624.

  Kwon, Sunghoon, Lee, Sangin and Kim, Yongdai (2015). Moderately clipped lasso. Computational Statistics and Data Analysis. 92, 53-67.

  Gwangsu Kim,, Jeongran Lee, Yongdai Kim, Heeseok Oh (2015). Sparse Bayesian representation in time-frequency domain. Journal of Statistical Planning and Inference. 166, 126-137.

  Ali, M., Kwon, Y.S., Lee, C.-H., Kim, J., Kim, Y. (Eds.). (2015), Current Approaches in Applied Artificial Intelligence; 28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2015, Seoul, South Korea, June 10-12, 2015, Proceedings, Lecture Note in Artificial Intelligence.

  Jae Chul Lee, Yongdai Kim, Jae-Won Soh and Byung-Joon Shin, (2014). Risk factors of adjacent segment disease requiring surgery after lumbar spinal fusion. Spine, 39, 339-345.

  Jae Chul Lee, Yongdai Kim, Jae-Won Soh and Byung-Joon Shin, (2014). Risk factors of adjacent segment disease requiring surgery after lumbar spinal fusion. Spine, 39, 339-345.

  Dan Shen, Haipeng Shen, Shankar Bhamidi, Yolanda Mu~noz Maldonado, Yongdai Kim and J.S. Marron (2014) Functional Data Analysis of Tree Data Objects. Journal of Computational and Graphical Statistics. 23, 418-438.

  Lan Wang, Yongdai Kim and Runze, Li . (2013) Calibrating non-convex penalized regression in ultra-high dimension. Annals of Statistics, 41, 2505-2536.

  Chae, Minwoo, Weissbach, Rafael, Cho, Kwang Hyun and Kim, Yongdai (2013), A mixture of beta-Dirichlet processes prior for Bayesian analysis of event history data, Journal of the Korean Statistical Society, volume 42 issue 3 September 2013 313-321.

  Kwon, Sunghoon, Kim, Yongdai and Choi, Hosik (2013). Sparse bridge estimation with a diverging number of parameters. Statistics and its Interface. 6, 231-242.

  Kim, Yongdai, Kim, Joungyoun and Jang, Woncheol. (2013). An EM algorithm for the proportional hazards model with doubly censored data. Computational Statistics and Data Analysis, 57, 41–51.

  Cha, Jang Gyu et al. (2012). Comparison of MRI T2 Relaxation Changes of Knee Articular Cartilage before and after Running between Young and Old Amateur Athletes, Korean Journal of Radiology, 13, 594-601.

  Lee, Sangin, Kim, Yongdai and Kwon, Sunghoon (2012). Quadratic approximation for nonconvex penalized estimations with a diverging number of parameters. Statistics and Probability Letters. 82(9), 1710-1717.

  Kim, Yongdai ,Kwon, Sunghoon, Choi Hosik (2012). Consistent Model Selection Criteria on High Dimensions. Journal of Machine Learning Research, 6(1), 1037-1057.

  Kim, Yongdai, James, Lancelot and Weissbach, Rafael. (2012). Bayesian analysis of a multi-state event history data: Beta-Dirichlet process. Biometrika. 99(1). 127-140.

  Kim, Yongdai and Kwon, Sunghoon (2012). Global optimality of nonconvex penalized estimators. Biometrika. 99(2). 315-325.

  Kwon, Sunghoon, and Kim, Yongdai (2012). Large sample properties of the SCAD penalized maximum likelihood estimator on high dimensions. Statistica Sinica. 22. 629-653.

  Lee, H.J. et al. (2011) A novel detection method of non-small cell lung cancer using multiplexed bead-based serum biomarker profiling. Journal of Thoracic and Cardiovascular Surgery. 143(2). 421-427.

  Kim, Yongdai, Kang, Byung Yup and Kim, Sungwook (2011). Component-wisely sparse boosting. Journal of the Korean Statistical Society. 40(4). 487-494.

  Jeon, Jong-June, Kim, Young-Oh and Kim, Yongdai (2011). Expected probability weighted moment estimator for censored flood data. Advances in Water Resources. 34(8). 933-945.

  Sunghoon Kwon, Hosik Choi, and Yongdai Kim (2011) Quadratic approximation on SCAD penalized estimation. Computational Statistics and Data Analysis. 55(1). 421-428.

  Kim, Yongdai and Kim, Dohyun (2011). Posterior consistency of random effects model for binary data. Journal of Statistical Planning and Inference. 141(11). 3391-3399.

  Kim, Yongdai, Park, Jinkyung and Kwangsoo Kim (2011). Bayesian analysis for monotone hazard ratio. Life Time Data Analysis. 17(2). 302-320.

  Choi, Hosik, Yeo, Dongwha, Kwon, Sunghoon and Kim, Yongdai. (2011). Gene selection and prediction for cancer classification using support vector machines with a reject option. Computational Statistics and Data Analysis. 55(5). 1897-1908.

  Kwon, Sunghoon and Kim, Yongdai (2011). Quadratic approximation for SCAD penalized estimation. Computational Statistics and Data Analysis. 55(1). 421-428.

  Kim, Yongdai, Kim, Bumsoo and Jang, Woncheol. (2010). Asymptotic properties of the maximum likelihood estimator for the proportional hazards model with doubly censored data. Journal of Multivariate Analysis, 101(6). 1339-1351.

  Yeon, Kyupil, Song, Moon Sup, Kim, Yongdai, Choi, Hosik, Park, Cheolwoo (2010). Model averaging via penalized regression for tracking concept drift. Journal of Computational and Graphical Statistics. 19(2). 457-473.

  Choi, Hosik and Kim, Yongdai (2010). A sparse large margin semi-supervised learning method. Journal of the Korean Statistical Society, 39(4). 479-487.

  Byoung-Kwon Kim, Jong Won Lee, Pil-je Park, Yong-Sung Shin, Won-Young Lee, Kyung-Ae Lee, Sena Ye, Heesun Hyun, Kyung-Nam Kang, Donghwa Yeo, Youngdai Kim, Sung-Yup Ohn, Dong-Young Noh and Chul-Woo Kim (2009) The multiplex bead array approach to identifying serum biomarkers associated with breast cancer. (2009) Breast Cancer Research. 11(2) R22.

  Kim, Yongdai, Kim, Yuwon, Kim, Jinseog, Sangin Lee and Sunghoon Kwon (2009) Boosting on the functional ANOVA decomposition. Statistics and Its Interface. 2. 361-368.

  Kim, Yongdai (2009) A Bernstein von Mises theorem for doubly censored data. Statistica Sinica. 19. 581-588.

  Kim, Yongdai and Kim, Dohyun. (2009). Bayesian partial likelihood approach for tied observations. Journal of Statistical Planning and Inference. 139(2). 467-477.

  Oh, Hee-Seok, Kim, Dongho and Kim, Yongdai (2009). Robust wavelet shrinkage using robust selection of thresholds. Statistics and Computing. 19(1). 27-34.

  Kim, Yongdai, Choi, Hosik and Oh, Heeseok (2008). Smoothly Clipped Absolute Deviation on High Dimensions. Journal of the American Statistical Association. 103. 1655-1673.

  Kim, Jinseog, Kim, Yuwon and Kim, Yongdai (2008). A gradient-based optimization algorithm for LASSO. Journal of Computational and Graphical Statistics. 17(4). 994-1009.

  Pillar, Ramani, Kim, Yongdai and Lee, Hakbae (2008) On casting random effects model in a survival framework. Journal of the Royal Statistical Society: Series B (Statistical Methodology). 70(3). 629-642.

  Lee, Jae Chul, Cha, Jang-Kyu, Kim, Yongdai, Kim, Yon-Il and Shin, Byung-Joon (2008). Quantitative Analysis of Back Muscle Degeneration in the Patients with the Degenerative Lumbar Flat Back using a Digital Image Analysis: Comparison with the normal controls. Spine, 33(3). 318-325.

  Kim, Yongdai, Kim, Yuwon and Kim, Jinseog. (2007). A gradient descent algorithm for LASSO. Contemporary Mathematics. 443. 73-82.

  Yi, Kwangkeun, Kim, Yongdai, Kim, Jaehwang, Choi, Hosik and Shin, Jaeho. (2007). An empirical study for classification methods for alarms from a Bug-Findings Static C analyzer. Information processing letters. 102(2-3). 118-123.

  Won, Youjip, Chang, Hyungkyu , Ryu, Jaemin , Kim, Yongdai and Shim, Junseok (2006) Intelligent Storage: Cross Layer Optimization for Soft Real-time Workload.ACM Trans on Storage. 2(3). 255-282.

  Kim, Yongdai, Kwon, Seonghoon, and Song, Seok Heun (2006) Multiclass sparse logistic regression for multiple cancer types using gene expression data. Computational Statistics and Data Analysis. 51(3). 1643-1655.

  Kim, Yongdai (2006) The Bernstien -von Mises theorem for the proportional hazard model. Annals of Statistics. 34(4). 1678-1700.

  Kim, Yuwon, Kim, Jinseog and Yongdai Kim (2006) Blockwise Sparse Regression. Statistica Sinica. 16. 375-390.

  Kim, Jinseog and Kim, Yongdai (2006) Maximum a posteriori pruning on decision tree and its application to bootstrap BUMPing. Computational Statistics and Data Analysis. 50(3). 710-719.

  Hwang, Hyungtae, So, Byungsoo and Kim, Yongdai (2005) On limiting posterior distributions. Test. 14(2). 567-580.

  Kim, Yongdai, Lee, Jaeyong and Kim, Jinseog (2005) Bayesian bootstrap for double censored data. Statistica Sinica. 15. 969-980.

  Kim, Yongdai and Kim, Jinseog (2004) Gradient LASSO for feature selection. Proceedings of the twenty-first international conference on machine learning. 473-480.

  Kim Yongdai, Kim, Jinseog and Jeon, Jongwoo (2004) Ensemble methods and rule generation. Intelligent Technologies for Information Analysis. Springer, 67-87.

  Kim, Yongdai and Kim, Jinseog (2004) Convex hull ensemble machine for regression and classification. Knowledge and Information Systems. 6(6). 645-663.

  Lee, Jaeyong and Kim, Yongdai (2004) A new algorithm to generate beta processes. Computational Statistics and Data Analysis. 47(3). 441-453.

  Park, Eunsik and Kim, Yongdai (2004) Analysis of longitudinal data in case control studies. Biometrika. 91(2). 321-330.

  Kim, Yongdai and Lee, Jaeyong (2004) A Bernstein von-Mises theorem in the nonparametric right-censored model. Annals of Statistics. 32. 1492-1512.

  Lee, Jaeyong and Kim, Yongdai. (2003) Statistical analysis of survival models with Bayesian bootstrap. Recent advances and Trends in Nonparametric Statistics. 411-420.

  Kim, Y. and Lee, J. (2003) Bayesian bootstrap for proportional hazards models. Annals of Statistics. 31(6). 1905-1922.

  Kim, Y. (2003) On posterior consistency of mixture of Dirichlet process with censored observations. Scandinavian Journal of Statistics. 30. 535-547.

  Kim, Y. (2003) Averaged Boosting: A new noise robust ensemble method, Lecture Note in Artificial Intelligience. 2637. 388-393.

  Kim, Y. and Lee, J. (2003) Bayesian analysis of proportional hazard models. Annals of Statistics. 31(2). 493-511.

  Kim, Y. (2002) Convex Hull Ensemble Machine. Proceedings of 2002 IEEE International Conference on Data Mining. 243-249.

  Kim, Y. et al. (2001) An outbreak of typhoid fever, Xing-An County, People's of Republic of China, 1999; Estimation of the field effectiveness of Vi Polysaccharide Typoid Vaccine. Journal of Infectious Disease. 183(12), 1775-1780.

  Kim, Y. and Lee, J. (2001) On posterior consistency of survival models. Annals of Statistics. 29(3). 666-686.

  Kim, Y and Lee, T. (1999) Time and state dependent failure rate model for software reliability. Proceedings of the Joint Statistical meetings. Baltimore, USA.

  Kim, Y. et al. (1999) Epidemiology of rota virus diarrhea in Egyptian children and implications for disease control. American Journal of Epidemiology. 150(7). 770-777.

  Kim, Y. et al. (1999) Early initiation of breast feeding and the risk of infant diarrhea in rural Egypt. Pediatrics. 104(1). e3-e3.

  Kim, Y. (1999) Nonparametric Bayesian estimators for counting processes. Annals of Statistics. 27(2). 562-588.

  Kim, Y. and Verducci, J. (1999) Too much sampling kills the UMP test. Statistics and Probability Letters. 41(2), 101-105.

  Kim, Y. (1998) Optimal estimation for continuous state branching processes with discrete sampling. Journal of Statistical Planning and Inference, 70(1). 77-89.

  Kim, Y. (1998) Mechanisms of symptom in Bartoszynski's virus model. Mathematical Bioscience. 153(1). 63-78.