Yichao Wu

Shen, K., & Wu, Y. (2022, October 18). Automatic structure recovery for generalized additive models. CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE. https://doi.org/10.1002/cjs.11739

Zheng, C., & Wu, Y. (2020). Nonparametric Estimation of Multivariate Mixtures. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 115(531), 1456–1471. https://doi.org/10.1080/01621459.2019.1635481

Zheng, C., & Wu, Y. (2020). Tuning parameter selection for penalised empirical likelihood with a diverging number of parameters. JOURNAL OF NONPARAMETRIC STATISTICS, 32(1), 246–261. https://doi.org/10.1080/10485252.2020.1717491

Kong, D., Bondell, H. D., & Wu, Y. (2018). FULLY EFFICIENT ROBUST ESTIMATION, OUTLIER DETECTION AND VARIABLE SELECTION VIA PENALIZED REGRESSION. STATISTICA SINICA, 28(2), 1031–1052. https://doi.org/10.5705/ss.202016.0441

Wang, C., Shin, S. J., & Wu, Y. (2018). Principal quantile regression for sufficient dimension reduction with heteroscedasticity. ELECTRONIC JOURNAL OF STATISTICS, 12(2), 2114–2140. https://doi.org/10.1214/18-EJS1432

Li, G., Nandgaonkar, A. G., Wang, Q., Zhang, J., Krause, W. E., Wei, Q., & Lucia, L. A. (2017). Laccase-immobilized bacterial cellulose/TiO2 functionalized composite membranes: Evaluation for photo- and bio-catalytic dye degradation. Journal of Membrane Science, 525, 89–98. https://doi.org/10.1016/j.memsci.2016.10.033

Shin, S. J., Wu, Y. C., Zhang, H. H., & Liu, Y. F. (2017). Principal weighted support vector machines for sufficient dimension reduction in binary classification. Biometrika, 104(1), 67–81.

Hu, H., Yao, W., & Wu, Y. (2017). The robust EM-type algorithms for log-concave mixtures of regression models. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 111, 14–26. https://doi.org/10.1016/j.csda.2017.01.004

Zhang, X., Wu, Y. C., Wang, L., & Li, R. Z. (2016). A consistent information criterion for support vector machines in diverging model spaces. Journal of Machine Learning Research, 17.

Peng, B., Wang, L., & Wu, Y. C. (2016). An Error bound for l-1-norm support vector machine coefficients in ultra-high dimension. Journal of Machine Learning Research, 17.

Chang, J., Tang, C. Y., & Wu, Y. (2016). LOCAL INDEPENDENCE FEATURE SCREENING FOR NONPARAMETRIC AND SEMIPARAMETRIC MODELS BY MARGINAL EMPIRICAL LIKELIHOOD. ANNALS OF STATISTICS, 44(2), 515–539. https://doi.org/10.1214/15-aos1374

Hu, H., Wu, Y., & Yao, W. (2016). Maximum likelihood estimation of the mixture of log-concave densities. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 101, 137–147. https://doi.org/10.1016/j.csda.2016.03.002

Zhang, C., Liu, Y. F., & Wu, Y. C. (2016). On quantile regression in reproducing kernel hilbert spaces with the data sparsity constraint. Journal of Machine Learning Research, 17.

Yao, F., Wu, Y. C., & Zou, J. L. (2016). Probability-enhanced effective dimension reduction for classifying sparse functional data. TEST, 25(1), 1–22.

Yao, F., Wu, Y., & Zou, J. (2016, March). Rejoinder on: Probability enhanced effective dimension reduction for classifying sparse functional data. TEST, Vol. 25, pp. 52–58. https://doi.org/10.1007/s11749-015-0478-7

Zhang, X., Wu, Y., Wang, L., & Li, R. (2016). Variable selection for support vector machines in moderately high dimensions. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 78(1), 53–76. https://doi.org/10.1111/rssb.12100

Wu, Y., & Stefanski, L. A. (2015). Automatic structure recovery for additive models. BIOMETRIKA, 102(2), 381–395. https://doi.org/10.1093/biomet/asu070

Xiao, W., Wu, Y., & Zhou, H. (2015). ConvexLAR: An Extension of Least Angle Regression. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 24(3), 603–626. https://doi.org/10.1080/10618600.2014.962700

Kong, D., Bondell, H. D., & Wu, Y. (2015). Domain selection for the varying coefficient model via local polynomial regression. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 83, 236–250. https://doi.org/10.1016/j.csda.2014.10.004

Yao, F., Lei, E., & Wu, Y. (2015). Effective dimension reduction for sparse functional data. BIOMETRIKA, 102(2), 421–437. https://doi.org/10.1093/biomet/asv006

Ke, Z. T., Fan, J., & Wu, Y. (2015). Homogeneity Pursuit. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 110(509), 175–194. https://doi.org/10.1080/01621459.2014.892882

Sun, W., Liu, Y., Crowley, J. J., Chen, T.-H., Zhou, H., Chu, H., … Villena, F. P.-M. (2015). IsoDOT Detects Differential RNA-Isoform Expression/Usage With Respect to a Categorical or Continuous Covariate With High Sensitivity and Specificity. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 110(511), 975–986. https://doi.org/10.1080/01621459.2015.1040880

Davenport, C. A., Maity, A., & Wu, Y. (2015). Parametrically guided estimation in nonparametric varying coefficient models with quasi-likelihood. JOURNAL OF NONPARAMETRIC STATISTICS, 27(2), 195–213. https://doi.org/10.1080/10485252.2015.1026903

Zhou, H., & Wu, Y. (2014). A Generic Path Algorithm for Regularized Statistical Estimation. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 109(506), 686–699. https://doi.org/10.1080/01621459.2013.864166

Avery, M., Wu, Y., Helen Zhang, H., & Zhang, J. (2014). RKHS-based functional nonparametric regression for sparse and irregular longitudinal data. CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 42(2), 204–216. https://doi.org/10.1002/cjs.11215

Shin, S. J., Wu, Y. C., & Zhang, H. H. (2014). Two-dimensional solution surface for weighted support vector machines. Journal of Computational and Graphical Statistics, 23(2), 383–402. https://doi.org/10.1080/10618600.2012.761139

Wu, S., Xue, H. Q., Wu, Y. C., & Wu, H. L. (2014). Variable selection for sparse high-dimensional nonlinear regression models by combining nonnegative garrote and sure independence screening. Statistica Sinica, 24(3), 1365–1387.

Shin, S. J., & Wu, Y. (2014, July). Variable selection in large margin classifier-based probability estimation with high-dimensional predictors. BIOMETRICAL JOURNAL, Vol. 56, pp. 594–596. https://doi.org/10.1002/bimj.201300251

Wu, Y., & Liu, Y. (2013). Adaptively Weighted Large Margin Classifiers. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 22(2), 416–432. https://doi.org/10.1080/10618600.2012.680866

Mueller, H.-G., Wu, Y., & Yao, F. (2013). Continuously additive models for nonlinear functional regression. BIOMETRIKA, 100(3), 607–622. https://doi.org/10.1093/biomet/ast004

Zeng, P., & Wu, Y. C. (2013). Coordinate great circle descent algorithm with application to single-index models. Statistics and Its Interface, 6(4), 511–518. https://doi.org/10.4310/sii.2013.v6.n4.a9

Wu, Y., & Liu, Y. (2013). Functional Robust Support Vector Machines for Sparse and Irregular Longitudinal Data. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 22(2), 379–395. https://doi.org/10.1080/10618600.2012.680823

Chang, J., Tang, C. Y., & Wu, Y. (2013). MARGINAL EMPIRICAL LIKELIHOOD AND SURE INDEPENDENCE FEATURE SCREENING. ANNALS OF STATISTICS, 41(4), 2123–2148. https://doi.org/10.1214/13-aos1139

Fan, J., Maity, A., Wang, Y., & Wu, Y. (2013). Parametrically guided generalised additive models with application to mergers and acquisitions data. JOURNAL OF NONPARAMETRIC STATISTICS, 25(1), 109–128. https://doi.org/10.1080/10485252.2012.735233

Wu, Y. C. (2012). Elastic net for Cox's proportional hazards model with a solution path algorithm. Statistica Sinica, 22(1), 271–294.

Wang, L., Wu, Y., & Li, R. (2012). Quantile Regression for Analyzing Heterogeneity in Ultra-High Dimension. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 107(497), 214–222. https://doi.org/10.1080/01621459.2012.656014

Wu, Y. (2011). An ordinary differential equation-based solution path algorithm. JOURNAL OF NONPARAMETRIC STATISTICS, 23(1), 185–199. https://doi.org/10.1080/10485252.2010.490584

Wu, Y. C., & Li, L. X. (2011). Asymptotic properties of sufficient dimension reduction with a diverging number of predictors. Statistica Sinica, 21(2), 707–730.

Liu, Y., Zhang, H. H., & Wu, Y. (2011). Hard or Soft Classification? Large-Margin Unified Machines. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 106(493), 166–177. https://doi.org/10.1198/jasa.2011.tm10319

Liu, Y., & Wu, Y. (2011). Simultaneous multiple non-crossing quantile regression estimation using kernel constraints. JOURNAL OF NONPARAMETRIC STATISTICS, 23(2), 415–437. https://doi.org/10.1080/10485252.2010.537336

Zhu, Z., & Wu, Y. (2010). Estimation and Prediction of a Class of Convolution-Based Spatial Nonstationary Models for Large Spatial Data. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 19(1), 74–95. https://doi.org/10.1198/jcgs.2009.07123

Wu, Y., Zhang, H. H., & Liu, Y. (2010). Robust Model-Free Multiclass Probability Estimation. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 105(489), 424–436. https://doi.org/10.1198/jasa.2010.tm09107

Shi, L. M., Campbell, G., Jones, W. D., Campagne, F., Wen, Z. N., Walker, S. J., … Du, P. (2010). The MicroArray Quality Control (MAQC)-IIII study of common practices for the development and validation of microarray-based predictive models. Nature Biotechnology, 28(8), 827–109.

Liu, Y. F., Wu, Y. C., & He, Q. Y. (2010). Utility-based weighted multicategory robust support vector machines. Statistics and its Interface, 3(4), 465–475. https://doi.org/10.4310/sii.2010.v3.n4.a5

Wu, Y., Fan, J., & Mueller, H.-G. (2010). Varying-coefficient functional linear regression. BERNOULLI, 16(3), 730–758. https://doi.org/10.3150/09-bej231

Ribeiro, C. M. P., Hurd, H., Wu, Y. C., Martino, M. E. B., Jones, L., Brighton, B., … O'Neal, W. K. (2009). Azithromycin treatment alters gene expression in inflammatory, lipid metabolism, and cell cycle pathways in well-differentiated human airway epithelia. PLoS One, 4(6).

Fan, J., Wu, Y., & Feng, Y. (2009). LOCAL QUASI-LIKELIHOOD WITH A PARAMETRIC GUIDE. ANNALS OF STATISTICS, 37(6B), 4153–4183. https://doi.org/10.1214/09-AOS713

Fan, J., Feng, Y., & Wu, Y. (2009). NETWORK EXPLORATION VIA THE ADAPTIVE LASSO AND SCAD PENALTIES. ANNALS OF APPLIED STATISTICS, 3(2), 521–541. https://doi.org/10.1214/08-AOAS215

Wu, Y. C., & Liu, Y. F. (2009). Stepwise multiple quantile regression estimation using non-crossing constraints. Statistics and Its Interface, 2(3), 299–310. https://doi.org/10.4310/sii.2009.v2.n3.a4

Fan, J. Q., Samworth, R., & Wu, Y. C. (2009). Ultrahigh dimensional feature selection: Beyond the linear model. Journal of Machine Learning Research, 10, 2013–2038.

Wu, Y. C., & Liu, Y. F. (2009). Variable selection in quantile regression. Statistica Sinica, 19(2), 801–817.

Fan, J., & Wu, Y. (2008). Semiparametric Estimation of Covariance Matrixes for Longitudinal Data. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 103(484), 1520–1533. https://doi.org/10.1198/016214508000000742