HOME /

Publications

Search
Author Title [ Type(Asc)] Year
Newspaper Article
Manuscript
Magazine Article
Zhu, M., 2010. Predictive analytics: Managing fundamental tradeoffs. Analytics, September-October, 2010, pp.18–21. Available at: http://viewer.zmags.com/publication/b0fd98bd#/b0fd98bd/19.
Zhu, M., 2008. How to draw a trilinear plot?. ASA Statistical Computing and Graphics Newsletter, 19, pp.7–9. Available at: http://stat-computing.org/newsletter/issues/scgn-19-1.pdf.
Journal Article
Hofert, M., Prasad, A. & Zhu, M., Accepted. RafterNet: Probabilistic predictions in multi-response regression. The American Statistician. Available at: https://doi.org/10.1080/00031305.2022.2141857.
Hofert, M., Prasad, A. & Zhu, M., Accepted. Dependence model assessment and selection with DecoupleNets. Journal of Computational and Graphical Statistics. Available at: https://doi.org/10.1080/10618600.2022.2157835.
Hofert, M., Prasad, A. & Zhu, M., 2022. Multivariate time-series modeling with generative neural networks. Econometrics and Statistics, 23, pp.147–164. Available at: https://doi.org/10.1016/j.ecosta.2021.10.011.
Hofert, M., Prasad, A. & Zhu, M., 2021. Quasi-random sampling for multivariate distributions via generative neural networks. Journal of Computational and Graphical Statistics, 30, pp.647–670. Available at: http://doi.org/10.1080/10618600.2020.1868302.
Wu, Y., Qin, Y. & Zhu, M., 2020. High-dimensional covariance matrix estimation using a low-rank and diagonal decomposition. Canadian Journal of Statistics, 48, pp.308–337. Available at: http://doi.org/10.1002/cjs.11532.
Hofert, M. et al., 2019. A framework for measuring association of random vectors via collapsed random variables. Journal of Multivariate Analysis, 172, pp.5–27. Available at: http://doi.org/10.1016/j.jmva.2019.02.012.
Zhang, C., Wu, Y. & Zhu, M., 2019. Pruning variable selection ensembles. Statistical Analysis and Data Mining: The ASA Data Science Journal, 12, pp.168–184. Available at: http://doi.org/10.1002/sam.11410.
Wu, Y., Qin, Y. & Zhu, M., 2019. Quadratic discriminant analysis for high-dimensional data. Statistica Sinica, 29, pp.939–960. Available at: http://doi.org/10.5705/ss.202016.0034.
Xin, L., Zhu, M. & Chipman, H.A., 2017. A continuous-time stochastic block model for basketball networks. Annals of Applied Statistics, 11, pp.553–597. Available at: http://doi.org/10.1214/16-AOAS993.
Zhu, M., 2015. Use of majority votes in statistical learning. Wiley Interdisciplinary Reviews: Computational Statistics, 7, pp.357–371. Available at: http://doi.org/10.1002/wics.1362.
Parissenti, A.M. et al., 2015. Tumor RNA disruption predicts survival benefit from breast cancer chemotherapy. Breast Cancer Research and Treatment, 153, pp.135–144. Available at: http://doi.org/10.1007/s10549-015-3498-9.
Yuan, Y., Su, W. & Zhu, M., 2015. Threshold-free measures for assessing the performance of medical screening tests. Frontiers in Public Health, 3, p.57. Available at: http://doi.org/10.3389/fpubh.2015.00057.
Soltan-Ghoraie, L., Burkowski, F. & Zhu, M., 2015. Sparse networks of directly coupled, polymorphic, and functional side chains in allosteric proteins. Proteins: Structure, Function, and Bioinformatics, 83, pp.497–516. Available at: http://doi.org/10.1002/prot.24752.

Pages