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Yoonkyung Lee

  • Professor, Computer Science & Engineering
  • Professor, Statistics
  • 1958 Neil Ave
    440H
    Columbus, OH 43210
  • 614-292-9495

Honors

  • August, 2015

    Fellow.

  • July, 2008

    Travel Award.

  • January, 2007-
    March, 2007

    Fellowship.

  • June, 2003

    Travel Award.

  • February, 2003

    Best Poster Award. Fredd State Technical College.

Chapters

2010

  • 2010. "Support vector machines for classification: A statistical portrait." In Statistical methods in molecular biology, edited by Bang, H., Zhou, X. K., Van Epps, H. L., and Mazumdar, M.,

Journal Articles

2017

2015

  • Lee, Y.; Wang, R., 2015, "Does modeling lead to more accurate classification?: A study of relative efficiency in linear classification." JOURNAL OF MULTIVARIATE ANALYSIS 133, 232-250 - 232-250.
  • Jung, Y.; Lee, Y.; MacEachern, S.N., 2015, "Efficient quantile regression for heteroscedastic models." JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 85, no. 13, 2548-2568 - 2548-2568.
  • Uematsu, K.; Lee, Y., 2015, "Statistical Optimality in Multipartite Ranking and Ordinal Regression." IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 37, no. 5, 1080-1094 - 1080-1094.

2014

  • Yao, Y. and Lee, Y., 2014, "Another look at linear programming for feature selection via methods of regularization." STATISTICS AND COMPUTING 24, no. 5, 885-905 - 885-905.
  • Liu, C., Shi, T., and Lee, Y., 2014, "Two tales of variable selection for high dimensional regression: Screening and model building." STATISTICAL ANALYSIS AND DATA MINING 7, 140-159 - 140-159.
  • Lee, Y., 2014, "Comments on: Support vector machines maximizing geometric margins for multi-class classification." TOP 22, no. 3, 852-855 - 852-855.

2013

  • Liang, Z.; Lee, Y., 2013, "Eigen-Analysis of Nonlinear PCA with Polynomial Kernels." STATISTICAL ANALYSIS AND DATA MINING 6, no. 6, 529-544 - 529-544.

2012

  • Lee, Y.; MacEachern, S.N.; Jung, Y., 2012, "Regularization of Case-Specific Parameters for Robustness and Efficiency." STATISTICAL SCIENCE 27, no. 3, 350-372 - 350-372.

2008

  • Koo, J.-Y., Lee, Y., Kim, Y., and Park, C., 2008, "A Bahadur representation of the linear support vector machine." JOURNAL OF MACHINE LEARNING RESEARCH 9, 1343-1368 - 1343-1368.
  • Rao, Y.; Lee, Y.; Jarjoura, D.; Ruppert, A.S. et al., 2008, "A comparison of normalization techniques for microRNA microarray data." STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY 7, no. 1,

2006

  • Lee, Y., 2006, "Semiparametric Regression by David Ruppert, M. P. Wand, and R. J. Carroll." JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION 101, 1722-1723 - 1722-1723.
  • Lee, Y.; Kim, Y.; Lee, S.; Koo, J-Y., 2006, "Structured multicategory support vector machines with analysis of variance decomposition." BIOMETRIKA 93, no. 3, 555-571 - 555-571.
  • Lee, Y.; Cui, Z., 2006, "Characterizing the solution path of multicategory support vector machines." STATISTICA SINICA 16, no. 2, 391-409 - 391-409.

2004

  • Lee, Y.K.; Lin, Y.; Wahba, G., 2004, "Multicategory support vector machines: Theory and application to the classification of microarray data and satellite radiance data." JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION 99, no. 465, 67-81 - 67-81.
  • Lee, Y.; Wahba, G.; Ackerman, S.A., 2004, "Cloud classification of satellite radiance data by multicategory support vector machines." JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY 21, no. 2, 159-169 - 159-169.

2003

  • Wahba, G.; Lin, Y.; Lee, Y.; Zhang, H., 2003, "Optimal properties and adaptive tuning of standard and nonstandard support vector machines." NONLINEAR ESTIMATION AND CLASSIFICATION 171, 129-147 - 129-147.

2002

  • Lin, Y.; Wahba, G.; Zhang, H.; Lee, Y., 2002, "Statistical properties and adaptive tuning of support vector machines." MACHINE LEARNING 48, no. 1-3, 115-136 - 115-136.
  • Lin, Y.; Lee, Y.; Wahba, G., 2002, "Support vector machines for classification in nonstandard situations." MACHINE LEARNING 46, no. 1-3, 191-202 - 191-202.

Unknown

  • Kim, J.; Lee, Y.; Liang, Z., "The Geometry of Nonlinear Embeddings in Kernel Discriminant Analysis."

Presentations

  • "Generalized Principal Component Analysis: Dimensionality Reduction through the Projection of Natural Parameters." 2015, Presented at Youngnam Mathematical Society Annual Meeting,
  • "Part I: Does Modeling Lead to More Accurate Classification?; Part II: Statistical Analysis of Bipartite and Multipartite Ranking by Convex Risk Minimization." 2010, Presented at Summer School on Statistical Pattern Recognition, CIMAT (Center of Research in Mathematics),
  • "A Bahadur Representation of the Linear Support Vector Machine." 2008, Presented at Data Mining and Statistical Learning Study Group, Department of Statistics, The Ohio State University,
  • "Comparison of the Efficiency of Classification Methods." 2010, Presented at Data Mining and Statistical Learning Study Group, Department of Statistics, The Ohio State University,
  • "Statistical Analysis of Bipartite and Multipartite Ranking by Convex Risk Minimization." 2010, Presented at Statistical Science - Making A Difference, 50th Anniversary Conference of the Department of Statistics,
  • "A Comparison of Classification Methods for Robustness." 2012, Presented at The Joint Statistical Meetings,
  • "A Short Course on Kernel Methods in a Regularization Framework." 2007, Presented at Winter School, CIMAT (Center of Research in Mathematics),
  • "Support Vector Machines for Classification: A Statistical Portrait." 2011, Presented at The Spring Conference of Korean Statistical Society,
  • "A Modern Look at Classical Multivariate Techniques (Part I: Regression, Part II: Classification, Part III: Dimensionality Reduction)." 2015, Presented at The 13th School of Probability and Statistics,
  • "A Tutorial on Kernel Methods in a Regularization Framework." 2008, Presented at Fall Conference of Korean Statistical Society,
  • "Kernel Methods in a Regularization Framework for Nonparametric Model Building." 2007, Presented at The Fall Workshop of ASA Cleveland Chapter,
  • "A Regularization Approach to Screening and Selection of Biomarkers." 2007, Presented at Department of Biostatistics, Washington University,
  • "A Bahadur Representation of the Linear Support Vector Machine." 2007, Presented at Department of Mathematics, Washington University,
  • "A Regularization Approach to Screening and Selection of Biomarkers." 2008, Presented at Department of Biostatistics and Bioinformatics, Emory University,
  • "Comparison of the Efficiency of Classification Methods." 2010, Presented at Department of Statistics, Indiana University,
  • "Comparison of the Efficiency of Classification Methods." 2010, Presented at Department of Food and Resource Economics, University of Delaware,
  • "Support Vector Machines for Classification: A Statistical Portrait." 2011, Presented at Department of Statistics, Hoseo University,
  • "A Study of Relative Efficiency and Robustness of Classification Methods." 2011, Presented at Department of Statistics, University of Seoul,
  • "Statistical Consistency of Multipartite Ranking." 2013, Presented at The Joint Statistical Meetings,
  • "A Bahadur Representation of the Linear Support Vector Machine." 2007, Presented at Department of Statistics, University of Georgia,
  • "Does Modeling Lead to More Accurate Classification?." 2010, Presented at ICSA Applied Statistics Symposium,
  • "Statistical Analysis of Bipartite Ranking by Convex Risk Minimization." 2011, Presented at KSS International Conference on Statistics and Probability,
  • "Another Look at Linear Programming for Feature Selection via Methods of Regularization." 2007, Presented at Department of Statistics, Korea University,
  • "Linear Programming for Feature Selection via Methods of Regularization." 2008, Presented at Statistical Research Center for Complex Systems, Seoul National University,
  • "Linear Programming for Feature Selection via Methods of Regularization." 2008, Presented at Department of Mathematical Information Science, Tokyo University of Science,
  • "Functional Component Pursuit." 2009, Presented at ICSA Applied Statistics Symposium,
  • "Functional Component Pursuit." 2009, Presented at The first Institute of Mathematical Statistics - Asia Pacific Rim Meeting,
  • "Functional Component Pursuit." 2009, Presented at Department of Statistics, University of Seoul,
  • "Support Vector Machines for Classification: A Statistical Portrait." 2011, Presented at Ulsan National Institute of Science and Technology,
  • "A Study of Relative Efficiency and Robustness of Classification Methods." 2011, Presented at Department of Statistics, Yonsei University,
  • "Error Bars?: Discussion of "Error Bars in Experimental Biology" by Cumming et al.(2007)." 2013, Presented at Molecular Genetics 7802 (Research Seminar: Cell Biology),
  • "A Statistical View of Ranking: Midway between Classification and Regression." 2014, Presented at Conference on Nonparametric Statistics for Big Data and Celebration to Honor Grace Wahba,
  • "Linear Programming for Feature Selection via Methods of Regularization." 2008, Presented at International Conference on Machine Learning and Data Mining,
  • "Another Look at Linear Programming for Feature Selection via Methods of Regularization." 2007, Presented at Department of Statistics, Carnegie Mellon University,
  • "A Regularization Approach to Screening and Selection of Biomarkers." 2008, Presented at ENAR,
  • "A Bahadur Type Representation of the Linear Support Vector Machine and its Relative Efficiency." 2009, Presented at Machine Learning Summer School (Theory and Practice of Computational Learning), University of Chicago,

Papers in Proceedings

2012

  • Lewis, J. R., MacEachern, S. N., and Lee, Y. "Robust inference via the blended paradigm." (12 2012).

2003

  • Lee, Y.; Lee, C.K. "Classification of multiple cancer types by tip multicategory support vector machines using gene expression data." in NIPS Workshop on Machine Learning Techniques for Bioinformatics. (6 2003).

2001

  • Lee, Y., Lin, Y., and Wahba, G. "Multicategory support vector machines." in 33rd Symposium on the Interface. (6 2001).