Hui Zou's Home Page

Publications

  • Xue, L. and Zou, H. (2012). Regularized Rank-based Estimation of High-dimensional Nonparanormal Graphical Models. Submitted

  • Xue, L., Ma, S. and Zou, H. (2011). Positive Definite L1 Penalized Estimation of Large Covariance Matrices. Submitted

  • Xue, L. and Zou, H. (2011). Sparse Estimation of Nonparanormal Covariance Matrices via Rank-based Thresholding. Submitted

  • Mai, Q. and Zou, H. (2011). Semiparametric Sparse Discriminant Analysis in Ultra-high Dimensions. Submitted

  • Xue, L. and Zou, H. (2011). Sure Independence Screening and Compressed Random Sensing. Biometrika, 98(2), 371-380.

  • Mai, Q., Zou, H. and Yuan, M. (2011). A Direct Approach to Sparse Discriminant Analysis in Ultra-high Dimensions. Biometrika, to appear. talk given at 2011 UFL winter workshop Jan 14--15

  • Ruan, L., Yuan, M. and Zou, H. (2011). Regularized Parameter Estimation in High-Dimensional Gaussian Mixture Models. Neural Computation, 23(6), 1605-1622.

  • Choi, J., Zou, H. and Oehlert, G. (2011). A Penalized Maximum Likelihood Approach to Sparse Factor Analysis. Statistics and Its Interface, 3(4), 429-436.

  • Kai, B., Li, R. and Zou, H. (2011). New Efficient Estimation and Variable Selection Methods for Semiparametric Varying-Coefficient Partially Linear Models. The Annals of Statistics, 39(1), 305-332. PDF

  • Xue, L., Zou, H. and Cai, T. (2010). Nonconcave penalized composite likelihood estimation of sparse Ising models. Technical Report 684, PDF

  • Zou, H. (2010). Discussion of ``Stability Selection" by Meichaushen and Buhlmann, Journal of the Royal Statistical Society, Series B.

  • Kai, B., Li, R. and Zou, H. (2010). Local CQR Smoothing: An Efficient and Safe Alternative to Local Polynomial Regression. Journal of the Royal Statistical Society, Series B, 72(1), 49-69.PDF

  • Yuan, M. and Zou, H. (2009). Efficient Global Approximation of Generalized Nonlinear L1-Regularized Solution Paths and Its Applications. Journal of the American Statistical Association, 104(488), 1562-1574.PDF

  • Yuan, M., Joseph, R. and Zou, H. (2009). Structured Variable Selection and Estimation, Annals of Applied Statistics, 3(4), 1738-1757.

  • Zhu, J., Zou, H., Rosset, S. and Hastie, T. (2009). Multi-class Adaboost. Statistics and Its Interface, 2(3), 349-360.

  • Zou, H. and Zhang, H. H. (2009). On The Adaptive Elastic-Net With A Diverging Number of Parameters. The Annals of Statistics, 37(4), 1733-1751.PDF

  • Zou, H. (2008). Discussion of ``Sure independence screening for ultra-high dimensional feature space'' by Fan and Lv, Journal of the Royal Statistical Society, Series B.

  • Zou, H., Zhu, J. and Hastie, T. (2008). New Multicategory Boosting Algorithms Based on Multicategory Fisher-Consistent Losses. Annals of Applied Statistics, 2(4), 1290-1306.PDF

  • Wu, S., Zou, H. and Yuan, M. (2008). Structured Variable Selection in Support Vector Machines. Electronic Journal of Statistics, 2, 103-117.

  • Zou, H. and Yuan, M. (2008). Regularized Simultaneous Model Selection in Multiple Quantiles Regression. Computational Statistics and Data Analysis, 52, 5296-5304.

  • Wang, L., Zhu, J. and Zou, H. (2008). Hybrid Huberized Support Vector Machines for Microarray Classification and Gene Selection. Bioinformatics, 24(3), 412-419.

  • Zou, H. and Yuan, M. (2008). Composite Quantile Regression and The Oracle Model Selection Theory. The Annals of Statistics, 36(3), 1108-1126.PDF

  • Zou, H. and Li, R. (2008). One-step Sparse Estimates in Nonconcave Penalized Likelihood Models. The Annals of Statistics (with discussion), 36(4), 1509-1533.PDF

  • Zou, H. (2008). A Note on Path-based Variable Selection in The Penalized Proportional Hazards Model. Biometrika, 95, 241-247.PDF

  • Zou, H. and Yuan, M. (2008). The F-infinity-norm Support Vector Machine. Statistica Sinica, 18, 379-398.PDF

  • Zou, H. (2007). An Improved 1-norm Support Vector Machine for Simultaneous Classification and Variable Selection. Eleventh International Conference on Artificial Intelligence and Statistics.

  • Zou, H., Zhu, J., Rosset, S. and Hastie, T. (2007). Automatic Bias Correction Methods in Semi-Supervised Learning. Contemporary Mathematics, 443, 165-175.

  • Zou, H., Hastie, T. and Tibshirani, R. (2007). On the Degrees of Freedom of the Lasso. The Annals of Statistics, 35(5) 2173-2192.PDF

  • Zou, H. (2006). The Adaptive Lasso And Its Oracle Properties. Journal of the American Statistical Association, 101(476), 1418-1429.PDF An Interview with ScienceWatch.com(Thomson Scientific)

  • Wang, L. and Zhu, J. and Zou, H. (2006). The Doubly Regularized Support Vector Machine. Statistica Sinica, 16(2), 589-616. PDF

  • Zou, H., Hastie, T. and Tibshirani, R. (2006). Sparse Principal Component Analysis. Journal of Computational and Graphical Statistics, 15(2), 265-286.PDF

  • Daniels, M. and Zhou, Z. and Zou, H. (2006). Conditionally Specified Space-Time Models for Multivariate Processes. Journal of Computational and Graphical Statistics, 15(1), 157-177.

  • Rosset, S., Zhu, J., Zou, H. and Hastie, T. (2005). A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning. Advances In Neural Information Processing Systems 17.

  • Zou, H. and Trevor, T. (2005). Regularization and Variable Selection via the Elastic Net. Journal of the Royal Statistical Society, Series B, 67(2), 301-320.PDF An Interview with Essential Science Indicators (Thomson Scientific)

  • Zou, H. and Yang, Y. (2004). Combining Time Series Models for Forecasting. International Journal of Forecasting, 20(1), 69-84.