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2016
Huggins, J., Campbell, T. & Broderick, T., 2016. Coresets for scalable Bayesian logistic regression. In Advances in Neural Information Processing Systems. Advances in Neural Information Processing Systems.
McPherson, A. & others, , 2016. Divergent modes of clonal spread and intraperitoneal mixing in high-grade serous ovarian cancer. Nature Genetics, 48, pp.758–767.
Cai, D., Campbell, T. & Broderick, T., 2016. Edge-exchangeable graphs and sparsity. In Advances in Neural Information Processing Systems. Advances in Neural Information Processing Systems.
Cai, S. & Chen, J., 2016. Empirical Likelihood Inference Under Density Ratio Models Based on Type I Censored Samples: Hypothesis Testing and Quantile Estimation. In Advanced Statistical Methods in Data Science. Advanced Statistical Methods in Data Science. Springer Singapore, pp. 123–151.
Tomal, J.H., Welch, W.J. & Zamar, R.H., 2016. Exploiting Multiple Descriptor Sets in QSAR Studies. Journal of chemical information and modeling, 56, pp.501–509. Available at: http://pubs.acs.org/doi/abs/10.1021/acs.jcim.5b00663.
Zhai, Y. & Bouchard-Côté, A., 2016. Inferring history of human populations using single-nucleotide polymorphism. Annals of Applied Stat, 10, pp.2047–2074.
Zhai, Y. & Bouchard-Côté, A., 2016. Inferring history of human populations using single-nucleotide polymorphism. Annals of Applied Statistics, 10, pp.2047–2074.
Kepplinger, D., Salibian-Barrera, M. & Freue, G.V.Cohen, 2016. Initial estimators for regularized robust methods in high-dimensional settings. In 22nd International Conference on Computational Statistics. 22nd International Conference on Computational Statistics.
Shaddick, G., Zidek, J.V. & Liu, Y., 2016. Mitigating the effects of preferentially selected monitoring sites for environmental policy and health risk analysis. Spatial and Spatio-temporal epidemiology, 18, pp.44-52.
Lau, K., Salibian-Barrera, M. & Lampe, L., 2016. Modulation recognition in the 868 MHz band using classification trees and random forests. {AEU} - International Journal of Electronics and Communications, 70, pp.1321 - 1328. Available at: http://www.sciencedirect.com/science/article/pii/S1434841116303430.
Chen, J. et al., 2016. Monitoring test under nonparametric random effects model. arXiv preprint arXiv:1610.05809.
Chen, J. et al., 2016. Monitoring test under nonparametric random effects model. arXiv preprint arXiv:1610.05809.
Joe, H. & Sang, P., 2016. Multivariate models for dependent clusters of variables with conditional independence given aggregation variables. Computational Statistics & Data Analysis, 97, pp.114-132.
Homrighausen, D. & McDonald, D.J., 2016. On the Nyström and Column-Sampling Methods for the Approximate Principal Components Analysis of Large Data Sets. Journal of Computational and Graphical Statistics, 25, pp.344–362. Available at: http://dx.doi.org/10.1080/10618600.2014.995799.
Mostafavi, S. et al., 2016. Parsing the Interferon Transcriptional Network and Its Disease Associations. Cell, 164, pp.564–578.

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