If you are looking for an early working paper, "Recall, Precision, and Average Precision",
cited by the article on "Information Retrieval" from Wikipedia,
please refer to and/or cite this published paper instead.

Newspaper column

Zhu M (2016). Tyranny in the name of science. In Ottawa Citizen, September 8, 2016, A8.

Journal articles, book chapters, and refereed conference proceedings

Wu Y, Qin Y, Zhu M (to appear). Quadratic discriminant analysis for high-dimensional data. Statistica Sinica, accepted.

Xin L, Zhu M, Chipman HA (2017). A continuous-time stochastic block model for basketball networks. The Annals of Applied Statistics, 11(2), 553 - 597.

Murdoch WJ, Zhu M (2016). Expanded alternating optimization for matrix factorization and penalized regression. In Proceedings of the 22nd International Conference on Computational Statistics, 217 - 229.

Zhu M (2015). Use of majority votes in statistical learning. Wiley Interdisciplinary Reviews: Computational Statistics, 7(6), 357 - 371.

Su W, Yuan Y, Zhu M (2015). A relationship between the average precision and the area under the ROC curve. In Proceedings of the ACM SIGIR 2015 International Conference on the Theory of Information Retrieval, 349 - 352.

Soltan-Ghoraie L, Burkowski F, Zhu M (2015). Using kernelized partial canonical correlation analysis to study directly coupled side chains and allostery in small G proteins. Bioinformatics, 31(12), i124 - i132.

Cheng L, Zhu M, Poss JW, Hirdes JP, Glenny C, Stolee P (2015). Opinion versus practice regarding the use of rehabilitation services in home care: An investigation using machine learning algorithms. BMC Medical Informatics and Decision Making, 15:80.

Yuan Y, Su W, Zhu M (2015). Threshold-free measures for assessing the performance of medical screening tests. Frontiers in Public Health, 3:57.

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(3), 497 - 516.

Armstrong JJ, Hirdes JP, Zhu M, Stolee P (2015). Rehabilitation therapies for older clients of the Ontario home care system: Regional variation and client-level predictors of service provision. Disability and Rehabilitation, 37(7), 625 - 631.

Soltan-Ghoraie L, Burkowski F, Li SC, Zhu M (2014). Residue-specific side-chain polymorphisms via particle belief propagation. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11(1), 33 - 41.

Zhu M (2014). Making personalized recommendations in e-commerce. In Statistics in Action: A Canadian Outlook, J. F. Lawless, Ed., Chapman & Hall, 259 - 268.

Zhu M, Cheng L, Armstrong JJ, Poss JW, Hirdes JP, Stolee P (2014). Using machine learning to plan rehabilitation for home care clients: Beyond "black-box" predictions. In Machine Learning in Healthcare Informatics, S. Dua, U. R. Acharya, P. Dua, Eds, Springer, 181 - 207. [***errata***]

Nguyen J, Zhu M (2013). Content-boosted matrix factorization techniques for recommender systems. Statistical Analysis and Data Mining, 6(4), 286 - 301.

Xin L, Zhu M (2012). Stochastic stepwise ensembles for variable selection. Journal of Computational and Graphical Statistics, 21(2), 275 - 294.

Zhu M, Wang S, Xin L (2012). On individual neutrality and collective decision making. The Mathematical Scientist, 37, 141 - 146. [arXiv:1204.5334]

Young SS, Yuan F, Zhu M (2012). Chemical descriptors are more important than learning algorithms for modeling. Molecular Informatics, 31(10), 707 - 710.

Armstrong JJ, Zhu M, Hirdes JP, Stolee P (2012). K-means cluster analysis of rehabilitation service users in the home health care system of Ontario: Examining the heterogeneity of a complex geriatric population. Archives of Physical Medicine and Rehabilitation, 93(12), 2198 - 2205.

Forbes P, Zhu M (2011). Content-boosted matrix factorization for recommender systems: Experiments with recipe recommendation. In Proceedings of the 5th ACM Conference on Recommender Systems, 261 - 264.

Su W, Chipman HA, Zhu M (2011). Pseudo-likelihood inference underestimates model uncertainty: Evidence from Bayesian nearest neighbours. Journal of the Iranian Statistical Society, 10(2), 167 - 180.

Zhu M, Fan G (2011). Variable selection by ensembles for the Cox model. Journal of Statistical Computation and Simulation, 81(12), 1983 - 1992.

Fan G, Zhu M (2011). Detection of rare items with TARGET. Statistics and Its Interface, 4(1), 11 - 17.

Gu H, Kenney T, Zhu M (2010). Partial generalized additive models: An information-theoretic approach for dealing with concurvity and selecting variables. Journal of Computational and Graphical Statistics, 19(3), 531 - 551.

Zhu M, Hastie TJ (2010). Letter to the editor. Journal of the American Statistical Association, 105(490), 880.

Hoshino R, Oldford RW, Zhu M (2010). Two-stage approach for unbalanced classification with time-varying decision boundary: Application to marine container inspection. In Proceedings of the ACM SIGKDD Workshop on Intelligence and Security Informatics, Washington, DC, USA, July 25, 2010.

Laflamme-Sanders A, Zhu M (2008). LAGO on the unit sphere. Neural Networks, 21(9), 1220 - 1223.

Zhu M (2008). Kernels and ensembles: Perspectives on statistical learning. The American Statistician, 62(2), 97 - 109.

Zhu M, Zhang Z, Hirdes JP, Stolee P (2007). Using machine learning algorithms to guide rehabilitation planning for home care clients. BMC Medical Informatics and Decision Making, 7:41.

Zhu M, Chen W, Hirdes JP, Stolee P (2007). The K-nearest neighbors algorithm predicted rehabilitation potential better than current clinical assessment protocol. Journal of Clinical Epidemiology, 60, 1015 - 1021.

Zhu M (2006). Discriminant analysis with common principal components. Biometrika, 93(4), 1018 - 1024.

Zhu M, Chipman HA (2006). Darwinian evolution in parallel universes: A parallel genetic algorithm for variable selection. Technometrics, 48(4), 491 - 502. [R code] [Technometrics invited session, INFORMS Annual Meeting, 2007]

Zhu M, Su W, Chipman HA (2006). LAGO: A computationally efficient approach for statistical detection. Technometrics, 48(2), 193 - 205. [R code] [Techometrics invited session, Joint Research Conference, 2006]

Zhu M, Ghodsi A (2006). Automatic dimensionality selection from the scree plot via the use of profile likelihood. Computational Statistics and Data Analysis, 51(2), 918 - 930. [R code]

Kustra R, Shioda R, Zhu M (2006). A factor analysis model for functional genomics. BMC Bioinformatics, 7:216.

Zhu M, Hastie TJ, Walther G (2005). Constrained ordination analysis with flexible response functions. Ecological Modelling, 187(4), 524 - 536. [***errata***]

Zhu M (2004). On the forward and backward algorithms of projection pursuit. The Annals of Statistics, 32(1), 233 - 244.

Zhu M, Lu AY (2004). The counter-intuitive non-informative prior for the Bernoulli family. Journal of Statistics Education, 12(2), online.

Zhu M, Hastie TJ (2003). Feature extraction for nonparametric discriminant analysis. Journal of Computational and Graphical Statistics, 12(1), 101 - 120. [***errata***]

Hastie TJ, Zhu M (2001). Discussion of "Dimension reduction and visualization in discriminant analysis" by Cook and Yin. Australian and New Zealand Journal of Statistics, 43(2), 179 - 185.

Refereed articles and abstracts from RNA Diagnostics, Inc.

Parissenti AM, Guo B, Pritzker LB, Pritzker KPH, Wang X, Zhu M, Shepherd LE, Trudeau ME (2015). Tumor RNA disruption predicts survival benefit from breast cancer chemotherapy. Breast Cancer Research and Treatment, 153, 135 - 144.

Trudeau ME, Pritzker LB, Parissenti AM, Wang X, Zhu M, Guo B, Shepherd LE, Chapman JW, Pritzker KPH (2012). A novel RNA test to guide primary systematic breast cancer chemotherapy. Annals of Oncology, 23(suppl 2), ii19.

Trade magazines, newsletters, bulletins, and others

Zhu M (2011). The impact of prediction contests. Contribution to the 2012 Long Range Plan for Mathematical and Statistical Sciences.

Zhu M (2010). Predictive analytics: Managing fundamental tradeoffs. Analytics, September-October 2010, 18 - 21. [PDF version]

Zhu M (2008). How to draw a trilinear plot? ASA Statistical Computing and Graphics Newsletter, 19(1), 7 - 9.

Preprints and newly submitted articles (aka technical reports)

Cheng L, Zhu M (2017). Compositional epistasis detection using a few prototype disease models. In revision.

Wu Y, Qin Y, Zhu M (2017). High-dimensional covariance matrix estimation using a low-rank and diagonal decomposition. Submitted.

Zhang C, Wu Y, Zhu M (2017). Pruning variable selection ensembles. Submitted.

Cheng H, Zhu M, Chan VW, Michela JL (2014). Single-index response surface models. Preprint. [R code]