Yichao Wu

Automatic structure recovery for generalized additive models

Shen, K., & Wu, Y. (2022, October 18). Canadian Journal of Statistics.

Tuning parameter selection for penalised empirical likelihood with a diverging number of parameters

Zheng, C., & Wu, Y. (2020, January 2). Journal of Nonparametric Statistics.

Nonparametric Estimation of Multivariate Mixtures

Zheng, C., & Wu, Y. (2019, June 25). Journal of the American Statistical Association.

Principal quantile regression for sufficient dimension reduction with heteroscedasticity

Wang, C., Shin, S. J., & Wu, Y. (2018, January 1). Electronic Journal of Statistics.

Fully efficient robust estimation, outlier detection, and variable selection via penalized regression

Bondell, H., Kong, D., & Wu, Y. (2017, April 18). Statistica Sinica.

Principal weighted support vector machines for sufficient dimension reduction in binary classification

Biometrika, 104(1), 67–81.

The robust EM-type algorithms for log-concave mixtures of regression models

Hu, H., Yao, W., & Wu, Y. (2017, February 3). Computational Statistics & Data Analysis.

A consistent information criterion for support vector machines in diverging model spaces

Journal of Machine Learning Research, 17.

An Error bound for l-1-norm support vector machine coefficients in ultra-high dimension

Journal of Machine Learning Research, 17.

Laccase-immobilized bacterial cellulose/TiO2 functionalized composite membranes: Evaluation for photo- and bio-catalytic dye degradation

Journal of Membrane Science, 525, 89–98.

Local independence feature screening for nonparametric and semiparametric models by marginal empirical likelihood

Chang, J., Tang, C. Y., & Wu, Y. (2016, March 23). The Annals of Statistics.

Maximum likelihood estimation of the mixture of log-concave densities

Hu, H., Wu, Y., & Yao, W. (2016, March 10). Computational Statistics & Data Analysis.

On quantile regression in reproducing kernel hilbert spaces with the data sparsity constraint

Journal of Machine Learning Research, 17.

Probability-enhanced effective dimension reduction for classifying sparse functional data

TEST, 25(1), 1–22.

Rejoinder on: Probability enhanced effective dimension reduction for classifying sparse functional data

Yao, F., Wu, Y., & Zou, J. (2016, January 25). Test.

Automatic structure recovery for additive models

Wu, Y., & Stefanski, L. A. (2015, March 11). Biometrika, Vol. 102, pp. 381–395.

Effective dimension reduction for sparse functional data

Yao, F., Lei, E., & Wu, Y. (2015, April 2). Biometrika.

Homogeneity Pursuit

Ke, Z. T., Fan, J., & Wu, Y. (2015, January 2). Journal of the American Statistical Association.

IsoDOT Detects Differential RNA-Isoform Expression/Usage With Respect to a Categorical or Continuous Covariate With High Sensitivity and Specificity

Sun, W., Liu, Y., Crowley, J. J., Chen, T.-H., Zhou, H., Chu, H., … Villena, F. P.-M. D. (2015, June 24). Journal of the American Statistical Association.

Parametrically guided estimation in nonparametric varying coefficient models with quasi-likelihood

Davenport, C. A., Maity, A., & Wu, Y. (2015, April 3). Journal of Nonparametric Statistics, Vol. 27, pp. 195–213.

Variable Selection for Support Vector Machines in Moderately High Dimensions

Zhang, X., Wu, Y., Wang, L., & Li, R. (2015, January 5). Journal of the Royal Statistical Society Series B (Statistical Methodology).

ConvexLAR: An Extension of Least Angle Regression

Xiao, W., Wu, Y., & Zhou, H. (2014, September 17). Journal of Computational and Graphical Statistics.

Domain selection for the varying coefficient model via local polynomial regression

Kong, D., Bondell, H. D., & Wu, Y. (2014, October 18). Computational Statistics & Data Analysis.

RKHS‐based functional nonparametric regression for sparse and irregular longitudinal data

Avery, M., Wu, Y., Zhang, H. H., & Zhang, J. (2014, May 6). Canadian Journal of Statistics.

Variable selection for sparse high-dimensional nonlinear regression models by combining nonnegative garrote and sure independence screening

Statistica Sinica, 24(3), 1365–1387.

Variable selection in large margin classifier‐based probability estimation with high‐dimensional predictors

Shin, S. J., & Wu, Y. (2014, February 25). Biometrical Journal.

A Generic Path Algorithm for Regularized Statistical Estimation

Zhou, H., & Wu, Y. (2013, December 3). Journal of the American Statistical Association.

Adaptively Weighted Large Margin Classifiers

Wu, Y., & Liu, Y. (2013, January 1). Journal of Computational and Graphical Statistics.

Continuously additive models for nonlinear functional regression

Muller, H.-G., Wu, Y., & Yao, F. (2013, March 26). Biometrika.

Coordinate great circle descent algorithm with application to single-index models

Wu, Y., & Zeng, P. (2013, January 1). Statistics and Its Interface.

Functional Robust Support Vector Machines for Sparse and Irregular Longitudinal Data

Wu, Y., & Liu, Y. (2013, January 1). Journal of Computational and Graphical Statistics.

Marginal empirical likelihood and sure independence feature screening

Chang, J., Tang, C. Y., & Wu, Y. (2013, August 1). The Annals of Statistics.

Two-Dimensional Solution Surface for Weighted Support Vector Machines

Shin, S. J., Wu, Y., & Zhang, H. H. (2013, January 23). Journal of Computational and Graphical Statistics.

Elastic net for Cox's proportional hazards model with a solution path algorithm

Statistica Sinica, 22(1), 271–294.

Parametrically guided generalised additive models with application to mergers and acquisitions data

Fan, J., Maity, A., Wang, Y., & Wu, Y. (2012, November 28). Journal of Nonparametric Statistics, Vol. 25, p. 109–128.

Quantile Regression for Analyzing Heterogeneity in Ultra-High Dimension

Wang, L., Wu, Y., & Li, R. (2012, March 1). Journal of the American Statistical Association.

Asymptotic properties of sufficient dimension reduction with a diverging number of predictors

Statistica Sinica, 21(2), 707–730.

Hard or Soft Classification? Large-Margin Unified Machines

Liu, Y., Zhang, H. H., & Wu, Y. (2011, March 1). Journal of the American Statistical Association.

Simultaneous multiple non-crossing quantile regression estimation using kernel constraints

Liu, Y., & Wu, Y. (2011, January 12). Journal of Nonparametric Statistics.

An ordinary differential equation-based solution path algorithm

Wu, Y. (2010, July 27). Journal of Nonparametric Statistics.

Estimation and Prediction of a Class of Convolution-Based Spatial Nonstationary Models for Large Spatial Data

Zhu, Z., & Wu, Y. (2010, January 1). Journal of Computational and Graphical Statistics.

Robust Model-Free Multiclass Probability Estimation

Wu, Y., Zhang, H. H., & Liu, Y. (2010, March 1). Journal of the American Statistical Association.

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.

Utility-based weighted multicategory robust support vector machines

He, Q., Liu, Y., & Wu, Y. (2010, January 1). Statistics and Its Interface.

Varying-coefficient functional linear regression

Wu, Y., Fan, J., & Müller, H.-G. (2010, August 1). Bernoulli.

Azithromycin treatment alters gene expression in inflammatory, lipid metabolism, and cell cycle pathways in well-differentiated human airway epithelia

PLoS One, 4(6).

Local quasi-likelihood with a parametric guide

Fan, J., Wu, Y., & Feng, Y. (2009, October 23). The Annals of Statistics.

Network exploration via the adaptive LASSO and SCAD penalties

Fan, J., Feng, Y., & Wu, Y. (2009, June 1). The Annals of Applied Statistics.

Stepwise multiple quantile regression estimation using non-crossing constraints

Liu, Y., & Wu, Y. (2009, January 1). Statistics and Its Interface.

Ultrahigh dimensional feature selection: Beyond the linear model

Journal of Machine Learning Research, 10, 2013–2038.

Variable selection in quantile regression

Statistica Sinica, 19(2), 801–817.

Semiparametric Estimation of Covariance Matrixes for Longitudinal Data

Fan, J., & Wu, Y. (2008, December 1). Journal of the American Statistical Association.