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Results for: Publications | Low-dimensional Representations Lab

Structure-leveraged methods in breast cancer risk prediction. Fan J, Wu Y, Yuan M, Page D, Liu J, Ong IM, Peissig P, Burnside E. Journal of Machine Learning Research 17:1-15, 2016.

Hypothesis testing in unsupervised domain adaptation with applications in neuroimaging. Zhou H, Ravi S, Ithapu V, Johnson S, Wahba G, Singh V. Advances in Neural Information Processing Systems (NIPS), 2016.

Minimax optimal rates of estimation in high dimensional additive models. Yuan M, Zhou D-X. Annals of Statistics 44(6):2564-2593, 2016.

Degrees of freedom in low rank matrix estimation. Yuan M. Science China Mathematics 59(12):2485–2502.

On tensor completion via nuclear norm minimization. Yuan M, Zhang C-H. Foundations of Computational Mathematics 16(4):1031–1068, 2016.

Minimax and adaptive estimation of covariance operator for random variables observed on a lattice graph. Cai T, Yuan M. Journal of the American Statistical Association 111(513):253-265, 2016.

Discriminatory power of common genetic variants in personalized breast cancer diagnosis. Wu Y, Abbey CK, Liu J, Ong I, Peissig P, Onitilo AA, Fan J, Yuan M, Burnside ES. Proceedings of the SPIE 9787 Medical Imaging, 2016.

Distance shrinkage and Euclidean embedding via regularized kernel estimation. Zhang L, Wahba G, Yuan M. Journal of the Royal Statistical Society B, doi:DOI: 10.1111/rssb.12138, 2016.

Comparing mammography abnormality features to genetic variants in the prediction of breast cancer in women recommended for breast biopsy. Burnside ES, Liu J, Wu Y, Onitilo AA, McCarty CA, Page CD, Peissig PL, Trentham-Dietz A, Kitchner T, Fan J, Yuan M. Academic Radiology 23(1):62–69, 2016.

Statistical significance of clustering using soft thresholding. Huang H, Liu Y, Yuan M, Marron J. Journal of Computational and Graphical Statistics 24(4):975-993.

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