Publications of Hui Zou

---

Journal Articles

• 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, In Press.
• Kai, B., Li, R. and Zou, H. (2009). Local CQR Smoothing: An Efficient and Safe Alternative to Local Polynomial Regression. Journal of the Royal Statistical Society, Series B, In Press.
• Yuan, M., Joseph, R. and Zou, H. (2009). Structured Variable Selection and Estimation, Annals of Applied Statistics, In Press.
• Zhu, J., Zou, H., Rosset, S. and Hastie, T. (2009) Multi-class Adaboost. Statistics and Its Interface, 2(3), 349-360. [a special issue on data mining and machine learning]
• 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'', Journal of the Royal Statistical Society, Series B. PDF
• 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. PDF
• Zou, H. and Yuan, M. (2008). Regularized Simultaneous Model Selection in Multiple Quantiles Regression. Computational Statistics and Data Analysis, 52, 5296-5304. PDF
• Wang, L., Zhu, J. and Zou, H. (2008). Hybrid Huberized Support Vector Machines for Microarray Classification and Gene Selection. Bioinformatics, 24(3), 412-419. PDF
• 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 Rejoinder
• 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., 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. [a special issue on data mining and machine learning] 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. PDF
• 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 EssentialScienceIndicators(Thomson Scientific)
• Zou, H. and Yang, Y. (2004). Combining Time Series Models for Forecasting. International Journal of Forecasting, 20(1), 69-84. PDF

Refereed Conference Papers

• 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.
• 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.