Published papers

International (underline: correspondence)

  • Lee et al. (2007). An empirical study on classification methods for alarms from a bug-finding static C analyzer, Information Processing Letters, 102(2-3): 118-123.
  • Kim, Y., Choi, H., Oh, H. (2008). Smoothly clipped absolutely deviation High-dimensions, Journal of the American Statistical Association, 103(484), 1665-1673.
  • Choi, H., Kim, J., Kim, Y. (2010). A sparse large margin semi-supervised learning method, Journal of the Korean Statistical Society, 39(4), 479-487.
  • Yeon et al. (2010). Model averaging via penalized regression for tracking concept drift, Journal of Computational and Graphical Statistics.
  • Kwon et al. (2011). Quadratic approximation on SCAD penalized estimation, Computational Statistics and Data Analysis, 55(1), 421-428.
  • Choi, H. et al. (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.
  • Kim et al. (2012). Predicting the fidelity of JPEG2000 compressed CT images using DICOM header information, Medical Physics, 38(12), 6449-6457.
  • Choi, H., Park, C. Y. (2012). Approximated penalization path for smoothly clipped absolute deviation, Journal of Statistical Computation and Simulation 18, 643–652.
  • Kim, Y., Kwon, S, Choi, H. (2012). Consistent model selection criteria on high dimensions, Journal of Machine Learning Research, 13, 1037-1057.
  • Kwon, S., Kim, Y., Choi, H. (2013). Sparse bridge estimation with diverging number of parameters, Statistics and its Interface, 6(2), 231-242.
  • Choi, H., Koo, J., Park, C. Y. (2015). Fused least absolute shrinkage and selection operator for credit scoring, Journal of Statistical Computation and Simulation, 85 (11), 2135-2147.
  • Won, S. et al. (2015). Evaluation of penalized and nonpenalized methods for disease prediction with large-scale genetic data, BioMed Research International.
  • Choi, H., Kim, Y., Kwon, S., Park, C. Y. (2017). A robust support vector machine for labeling errors, Communications in Statistics: Simulation and Computation, 46 (8), 6061-6073.
  • Wang, L, Park, C. W., Yeon, K., Choi, H. (2017). Tracking concept drift using a constrained penalized regression combiner, Computational Statistics and Data Analysis, 108, 52-69.
  • Jeon, J-J., Kwon, S., Choi, H. (2017). Homogeneity detection for the high-dimensional generalized linear model, Computational Statistics and Data Analysis, 114, 61-74.
  • Gim, J. et al. (2017). Incorporating family disease history in risk prediction models with large-scale genetic data, Genetics,
  • Choi, H., Gim, J., Won, S., Kwon, S., and Park, C. Y. (2017). Network analysis for count data with excess zeros, BMC Genetics, 18(1).
  • Jeon, J-J., Choi, H. (2018). Sparse Luce Model, Applied Intelligence, 48(8), 1953–1964.
  • Choi, H., Eong, E., Hwang, S., and Lee, W. (2018). A modified generalized lasso algorithm to detect local spatial clusters for count data, AStA Advances in Statistical Analysis, 102 (4), 537-563.
  • Wang et al. (2019). Regularized aggregation of statistical parametric maps, Human Brain Mapping, 40(1), 65-79.
  • Liao, L., Park, C., and Choi, H. (2019). Penalized expectile regression: an alternative to penalized quantile regression, Annals of the Institute of Statistical Mathematics, 71 (2), 409-438.
  • Choi, H., Poythress, JC., Park, C., Jeon, J-J., Park, C. (2019). Regularized boxplot via convex clustering , Journal of Statistical Computation and Simulation, 89(7), 1227-1247.
  • Park, C., Choi, H., Delcher, C., Wang, Y., and Yoon, Y.J. (2019+). Convex Clustering Analysis for Histogram‐Valued Data, Biometrics, in press.
  • Choi, H. and Lee, S. (2019+). Convex clustering for binary data, Advances in Data Analysis and Classification, in press.
  • Jeon, J-J., Kim, Y., Won, S. Choi, H. (2019). Primal path algorithm for compositional data analysis, arXiv:1812.08954.

Domestic

  • An extension of COSSO algorithm by Combining Variables, Journal of the Korean Data Analysis Society, 2007.10
  • 산부인과 진뢰 의뢰서의 추정진단명과 최종 진단명의 일치율에 관한 연구, Journal of the Korean Data Analysis Society, 2008.08
  • The doubly regularized quantile regression, Communications on the Korean Statistical Society, 753-763, 2008.09
  • Quantile regression with non-convex penalty on high-dimensions, Communications on the Korean Statistical Society, 209-215, 2009.01
  • 지분된 범주를 가진 분류문제에 대한 계층적분류분석 방법, Journal of the Korean Data Analysis Society 339-348, 2009.02
  • 보험사의 고객이탈에 대한 예측모형개발, Journal of the Korean Data Analysis Society, 2009.02
  • 고객 스코어링 캠페인 시스템 개발에 관한 연구, 응용통계연구, 2009.02
  • 데이터마이닝과 마켓팅리서치에서 토빗모형의 응용에 관한 사례 연구, Journal of the Korean Data Analysis Society, 2009.02
  • An algorithm for support vector machines with a rejection option using bundle method, Communications on the Korean Statistical Society, 997-1004, 2009.11
  • The unified framework for AUC maximizer, Communications on the Korean Statistical Society, 1005-1012, 2009.11
  • 부동산 경매지수의 개발, Journal of the Korean Data Analysis Society, 2009.12
  • 상관성 회귀모형에 대한 비교연구, Journal of the Korean Data Analysis Society, 3319-3330, 2009.12
  • 판정보류 옵션을 가진 분류자, Journal of the Korean Data Analysis Society, 12(6), 3317-3325, 2010.12
  • 한국교육종단연구 데이터에 대한 위계적 선형모형의 적용, Journal of the Korean Data Analysis Society, 13(2), 833 – 844, 2011.04.30
  • 소지역 추정방법을 이용한 구매액 예측에 관한 연구, Journal of the Korean Data Analysis Society, 13(4), 1837 – 1848, 2011.08
  • 고객 세그먼트별 리스크 관리를 위한 신용평점모형 개발에 관한 연구, Journal of the Korean Data Analysis Society, 14(4), 1839 – 1848, 2012.08.31
  • 이단계 군집분석을 활용한 고객세분화, Journal of the Korean Data Analysis Society, 14(4), 1849 – 1860, 2012.08.31
  • 경시적 자료에 대한 분위수 회귀 축소추정방법, Journal of the Korean Data Analysis Society, 757-766, 2012.04.30
  • 선형회귀모형에서의 이상치 탐색방법들의 비교연구, Journal of the Korean Data Analysis Society, 177-186, 15(1), 2013.02.28
  • 빅 데이터 분석을 위한 지지벡터기계, 한국데이터정보과학회지, 2013.08.31
  • Spatial clustering method via generalized lasso, 응용통계연구, 2014
  • A Sparse Ridge Estimation for the Sparse Logistic Regression Models, Journal of the Korean Data Analysis Society, 2014
  • 커피전문점 선택속성과 시장세분화에 관한 연구: 의사결정나무분석을 이용하여, 관광레저연구, 27, 269-288, 2015
  • 축소된 상자그림을 활용한 미세먼지 데이터의 군집분석, Journal of the Korean Data Analysis Society, 18(5), 2435-2443, 2016.10.
  • 최호식 (2017). 단조증가 제약식을 가진 단순회귀분석 방법과 응용, Journal of the Korean Data Analysis Society, 19(5), 2395-2404.
  • 최호식,최현집,박상언 (2017). 통계적 기계학습에서의 ADMM 알고리즘의 활용, Journal of the Korean Data and Information Science Society.
  • 최호식 (2019). 종분류 그룹정보를 활용한 혈류감염 마이크로바이옴 자료의 분류방법(Classification of bloodstream infection microbiome data using group information in Taxonomy), Journal of the Korean Data Analysis Society, 21(2), 651-659.
  • 권성훈, 조진연, 최호식, 이상인 (2019). Variable Selection via the Sparse Net, Journal of The Korean Data Analysis Society, 21(3), 1111-1120.

Book

  • 마이크로어레이 자료의 통계적 분석, 서울대학교 통계학과 생물정보통계연구실, 자유아카데미, 2005.05
  • SPSS(PASW statistics) 데이터 분석입문, 자유아카데미, 2010.11
  • R을 이용한 데이터마이닝, 교우사, 2011.07, 2015.03(개정), 저서