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Results for: Publications | Low-dimensional Representations Lab


Utility of genetic testing in addition to mammography for determining risk of breast cancer depends on patient age. Feld S, Fan J, Yuan M, Wu Y, Woo K, Alexandridis R, Burnside E. Proceedings of the AMIA Informatics Summit, 2018.

Quantifying predictive capability of electronic health records for the most harmful breast cancer. Wu Y, Fan J, Peissig P, Berg R, Tafti P, Yin J, Yuan M, Page D, Cox J, Burnside E. Proceedings of SPIE Medical Imaging, 2018.

Statistical tests and identifiability conditions for pooling and analyzing multisite datasets. Zhou HH, Singh V, Johnson SC, Wahba G, and the Alzheimer’s Disease Neuroimaging Initiative. Proceedings of the National Academy of Sciences USA, 2018.

Automated and robust quantification of colocalization in dual-color fluorescence microscopy: A nonparametric statistical approach. Wang S, Arena E, Elicieri K, Yuan M. IEEE Transactions on Image Processing 27(2):622-636, 2018.

Screening rule for L1-regularized Ising model estimation. Kuang Z, Geng S, Page D. Advances in Neural Information Processing Systems Conference (NIPS), 2017.

Incoherent tensor norms and their applications in higher order tensor completion. Yuan M, Zhang C-H. IEEE Transactions on Information Theory 63(10):6753 - 6766, 2017 .

Global testing against sparse alternatives under Ising models. Mukherjee R, Mukherjee, Yuan M. To appear in Annals of Statistics, 2018.

When can multi-site datasets be pooled for regression? Hypothesis tests, L2-consistency and neuroscience applications. Zhou HH, Zhang Y, Ithapu VK, Johnson SC, Wahba G, Singh V. Proceedings of the International Conference on Machine Learning (ICML), 2017.

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.

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