Zhu, Y. and Liu, R. (2023). Path following algorithms for -regularized M-estimation with approximation guarantee. Advances in Neural Information Processing Systems (NeurIPS). Accepted.
Zhu, Y., Shen, X., Jiang, H., and Wong, W. (2022). Collaborative multilabel classification. Journal of the American Statistical Association: Theory and Methods. Accepted.
Liu, R. and Zhu, Y. (2022). On the consistent estimation of Receiver Operating Characteristic (ROC) curve. Advances in Neural Information Processing Systems (NeurIPS). Accepted.
Luan, B., Lee, Y., and Zhu, Y. (2022). On Measuring Model Complexity in Heteroscedastic Linear Regression. arXiv preprint arXiv:2204.07021.
Zhu, Y. and Liu, R. (2021). An algorithmic view of L2 regularization and some path-following algorithms. Journal of Machine Learning Research. Accepted.
Luan, B., Lee, Y., and Zhu, Y. (2021). Predictive Model Degrees of Freedom in Linear Regression. arXiv preprint arXiv:2106.15682.
Zhu, Y. (2020). A convex optimization formulation for multivariate linear regression. Advances in Neural Information Processing Systems (NeurIPS).
Che, Y., Zhu, Y., and Shen, X. (2020). Multilabel classification with multivariate time series predictors, The IEEE Transactions on Signal Processing, 68, 5696-5705. [website]
Zhu, Y., Shen, X., Pan, W. (2020). On high-dimensional constrained maximum likelihood inference. Journal of American Statistical Association, 155(529), 217-230. [website]
Tang, S., Craigmile, P., and Zhu, Y. (2019). Spectral estimation using multitaper Whittle methods with a lasso penalty. IEEE Transactions on Signal Processing, 67(19), 4992-5003. [website]
Zhu, Y. and Li, L. (2018). Multiple matrix Gaussian graphs estimation. Journal of the Royal Statistical Society, Series B. [website]
Zhu, Y. (2017). An augmented ADMM algorithm with application to the generalized lasso problem. Journal of Computational and Graphical Statistics, 26(1), 195-204. [website]
Gao, C., Zhu, Y., Shen, X., and Pan, W. (2016). Estimation of multiple networks in Gaussian mixture models. Electrical Journal of Statistics. 10, 1133-1154. [website]
Zhu, Y., Shen, X., Ye, C. (2016). Personalized prediction and sparsity pursuit in latent factor models. Journal of American Statistical Association, 111(513), 241-252. [website]
Zhu, Y., Shen, X., Pan, W. (2014). Structural pursuit over multiple undirected graphs. Journal of American Statistical Association, 109(508), 1683-1696.[website]
Zhu, Y., Shen, X., Pan, W. (2013). Simultaneous grouping pursuit and feature selection over an undirected graph. Journal of American Statistical Association, 108(502), 713-725. [website]
Shen, X., Pan, W., Zhu, Y., and Zhou, H. (2013). On constrained and regularized high-dimensional regression. The Annals of the Institute of Statistical Mathematics,1, 1-26. [website]
Shen, X., Pan, W., Zhu, Y. (2012). Likelihood-based selection and sharp parameter estimation. Journal of the American Statistical Association, 107(497), 223-232. [website]
Xiang, S., Zhu, Y., Shen, X., Ye, J. (2012). Optimal exact rank minimization for noisy data. KDD’12 Proceedings of the 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 480-488. [website]
Zhu, Y., Wang, G., Yang, J., Wang, D., Yan, J., Hu, J. and Chen, Z. (2009). Optimizing search engine revenue in sponsored search. In Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval (pp. 588-595). ACM. [website]
Zhu, Y., Wang, G., Yang, J., Wang, D., Yan, J. and Chen, Z. (2009). Revenue optimization with relevance constraint in sponsored search. In Proceedings of the Third International Workshop on Data Mining and Audience Intelligence for Advertising (pp. 55-60). ACM.
Wang, G., Hu, J., Zhu, Y., Li, H., and Chen, Z. (2009, April). Competitive analysis from click-through log. In Proceedings of the 18th international conference on World wide web (pp. 1051-1052). ACM.