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Yoonkyung Lee Publications

BibTeX entries for the following papers are available here.

Technical Reports and Manuscripts

  1. Generalized Principal Component Analysis: Projection of Saturated Model Parameters - Landgraf, A. J. and Lee, Y., June 2015, Technical Report No. 892, Department of Statistics, The Ohio State University. Revised February 2016. Revised May 2017. An R implementation of the generalized PCA algorithms described in the paper is available at
    github.com/andland/generalizedPCA.

  2. Dimensionality Reduction for Binary Data through the Projection of Natural Parameters - Landgraf, A. J. and Lee, Y., April 2015, Technical Report No. 890, Department of Statistics, The Ohio State University.
    The latest version with some updates on Section 5.2 is also available at arXiv:1510.06112.
    An R implementation of the logistic PCA algorithms described in the paper is available at
    cran.r-project.org/web/packages/logisticPCA and github.com/andland/logisticPCA.

  3. Comments on Support vector machines maximizing geometric margins for multi-classification - Lee, Y., May 2014.
    TOP (an official journal of the Spanish Society of Statistics and Operations Research), Volume 22, Issue 3, 852-855, 2014.

  4. Bayesian Restricted Likelihood Methods - Lewis, J. R., MacEachern, S. N., and Lee, Y., May 2014, Technical Report No. 878, Department of Statistics, The Ohio State University.

  5. Efficient Quantile Regression for Heteroscedastic Models - Jung, Y., Lee, Y., and MacEachern, S. N., March 2014, Technical Report No. 877, Department of Statistics, The Ohio State University. Revised August 2014. It has appeared in Journal of Statistical Computation and Simulation, Volume 85, Issue 13, 2548-2568, 2015.

  6. Statistical Optimality in Multipartite Ranking and Ordinal Regression - Uematsu, K., and Lee, Y., August 2013, Technical Report No. 873, Department of Statistics, The Ohio State University. It has appeared in IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 37, No. 5, 1080-1094, May 2015.

  7. Eigen-Analysis of Nonlinear PCA with Polynomial Kernels - Liang, Z. and Lee, Y., October 2012, Technical Report No. 872, Department of Statistics, The Ohio State University. Revised May 2013. It has appeared in Statistical Analysis and Data Mining, Volume 6, Issue 6, 529-544, 2013.

  8. Robust Inference via the Blended Paradigm - Lewis, J. R., MacEachern, S. N. and Lee, Y., September 2012. In the Proceedings of the Joint Statistical Meetings, 1773-1786, 2012.

  9. Does Modeling Lead to More Accurate Classification?: A Study of Relative Efficiency - Lee, Y. and Wang, R., July 2012, Technical Report No. 869, Department of Statistics, The Ohio State University. Revised May 2013. Revised November 2013. It has appeared in Journal of Multivariate Analysis, Volume 133, 232-250, 2015.

  10. Two Tales of Variable Selection for High Dimensional Regression: Screening and Model Building - Liu, C., Shi, T., and Lee, Y., July 2012, Technical Report No. 868, Department of Statistics, The Ohio State University. Revised October 2013. Statistical Analysis and Data Mining, Volume 7, Issue 2, 140-159, 2014.

  11. On Theoretically Optimal Ranking Functions in Bipartite Ranking - Uematsu, K., and Lee, Y., December 2011, Technical Report No. 863, Department of Statistics, The Ohio State University. Revised November 2012. Published online August 2016. Click here for eprints. It has appeared in Journal of the American Statistical Association, Volume 112, Number 519, 1311-1322, 2017.

  12. Window Width Selection for L2 Adjusted Quantile Regression - Jung, Y., MacEachern, S. N., and Lee, Y., April 2010, Technical Report No. 835, Department of Statistics, The Ohio State University.

  13. Determination of Sample Size for Validation Study in Pharmacogenomics - Rao, Y., Lee, Y., and Hsu, J. C., January 2010, Technical Report No. 834, Department of Statistics, The Ohio State University.
    R code for sample size calculation (written by Youlan Rao).

  14. Support Vector Machines for Classification: A Statistical Portrait - Lee, Y.
    In Statistical Methods in Molecular Biology, Heejung Bang, Xi Kathy Zhou, Heather L. Van Epps, and Madhu Mazumdar, eds, in the series of Methods in Molecular Biology, Humana Press, 347-368, 2010. [Errata]

  15. Design and Analysis of Microarray Experiments for Pharmacogenomics - Hsu, J. C., Rao, Y., Lee, Y., Chang, J., Bergsteinsdottir, K., Magnusson, M.K., Wang, T., Steingrimsson, E. In Multiple Testing Problems in Pharmaceutical Statistics, Dmitrienko, A., Tamhane, A.C., Bretz, F., eds., Chapman & Hall/CRC Biostatistics Series, 2009. [A version in the Book]

  16. Regularization of Case-Specific Parameters for Robustness and Efficiency - Lee, Y., MacEachern, S. N., and Jung, Y., July 2007, Technical Report No. 799, Department of Statistics, The Ohio State University. Revised December 2009. Revised April 2011. Statistical Science, Vol. 27, No. 3, 350-372, 2012.

  17. Another Look at Linear Programming for Feature Selection via Methods of Regularization - Yao, Y., and Lee, Y., July 2007, Technical Report No. 800, Department of Statistics, The Ohio State University. Revised November 2007. Revised April 2010 and December 2012. Statistics and Computing, (June 2013 online) Vol. 24, Issue 5, 885-905, 2014.

  18. A Comparison of Normalization Techniques for MicroRNA Microarray Data - Rao, Y., Lee, Y., Jarjoura, D., Ruppert, A. S., Liu, C., Hsu, J. C., and Hagan, J. P., February 2007. Revised February 2008. Statistical Applications in Genetics and Molecular Biology, Vol. 7 : Issue 1, Article 22, 2008. *

  19. A Bahadur Representation of the Linear Support Vector Machine - Koo, J.-Y., Lee, Y., Kim, Y., and Park, C., December 2006, Technical Report No. 792, Department of Statistics, The Ohio State University. Revised February 2008. Journal of Machine Learning Research, vol. 9, 1343-1368, 2008.

  20. Characterizing the Solution Path of Multicategory Support Vector Machines - Lee, Y. and Cui, Z., April 2005, Technical Report No. 754, Department of Statistics, The Ohio State University. TR 754rr, revised December 2005. Statistica Sinica, vol. 16, No. 2, 391-409, 2006.

  21. Structured Multicategory Support Vector Machine with ANOVA decomposition - Lee, Y., Kim, Y., Lee, S., and Koo, J.-Y., October 2004, Technical Report No. 743, Department of Statistics, The Ohio State University. TR 743rr, revised November 2005. It has appeared in Biometrika, vol. 93, No. 3, 555-571, 2006.
    SMSVM implementation in R.

  22. Classification of Satellite Radiance Data by Multicategory Support Vector Machines - Lee, Y., Wahba, G., and Ackerman, S., February 2003, Technical Report 1075. Department of Statistics, University of Wisconsin-Madison. Revised version has appeared in Journal of Atmospheric and Oceanic Technology (JTECH), vol. 21 (2), 159-169, 2004.

  23. Multicategory Support Vector Machines, Theory, and Application to the Classification of Microarray Data and Satellite Radiance Data - Lee, Y., Lin, Y., and Wahba, G., September 2002, Technical Report 1064. Department of Statistics, University of Wisconsin-Madison. TR 1064r, Revised May 2003. TR 714, Revised August 2003, Technical Report 714, Department of Statistics, The Ohio State University.
    Journal of the American Statistical Association as the lead paper in the Theory and Methods section, vol. 99, 67-81, 2004.

  24. Classification of Multiple Cancer Types by Multicategory Support Vector Machines Using Gene Expression Data - Lee, Y. and Lee, C.-K., Bioinformatics, vol. 19 (9), 1132-1139, 2003. [Supplementary Information]
    Part of the work presented at ENAR meeting held in Crystal City VA, March 2002.

  25. Optimal Properties and Adaptive Tuning of Standard and Nonstandard Support Vector Machines- Wahba, G., Lin, Y., Lee, Y., and Zhang, H., October 2001. Technical Report 1045. In Nonlinear Estimation and Classification, Denison, D. D., Hansen, M. H., Holmes, C. C., Mallick, B., and Yu, B., eds, Springer, New York, 129-147, 2003.

  26. Statistical Properties and Adaptive Tuning of Support Vector Machines - Lin, Y., Wahba, G., Zhang, H., and Lee, Y., 2000. Technical Report 1022. Machine Learning, 48, 115-136, 2002.

  27. Support Vector Machines for Classification in Nonstandard Situations - Lin, Y., Lee, Y., and Wahba, G., 2000. Technical Report 1016. Machine Learning, 46, 191-202, 2002.

  28. Multicategory Support Vector Machines - Lee, Y., Lin, Y. and Wahba, G., Technical Report 1043, September, 2001. Computing Science and Statistics 33, 498-512, 2001. Presented in Interface '01, Costa Mesa CA June 2001.

Others

  1. Book Review : Semiparametric Regression by David Ruppert, M. P. Wand, and R. J. Carroll.
    - Lee, Y., Journal of the American Statistical Association, vol. 101, 1722-1723, 2006.

  2. Multicategory Support Vector Machines, Theory, and Application to the Classification of Microarray Data and Satellite Radiance Data - Lee, Y., August 2002, Ph.D. thesis, Department of Statistics, University of Wisconsin-Madison. Technical Report 1063.

  3. On Optimal Primer Design for Identifying Novel Molecular Sequences in Biodiversity Studies - Newton, M., Lee, Y., Chelius, M., and Triplett, E., 1999. Abstract in Statistical Society of Canada 1999.

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