Contact Information:
Department of Statistics University of Michigan keanming @ umich.edu |
I am currently an assistant professor at the Department of Statistics at University of Michigan. Previously, I was an assistant professor at the School of Statistics at University of Minnesota, and a postdoctoral research associate supervised by Han Liu and Tong Zhang. Prior to this, I obtained my PhD degree in the Department of Biostatistics at University of Washington, under the supervision of Daniela Witten.
I am an applied statistician working on statistical machine learning methods for analyzing complex biomedical data sets. I develop multivariate statistical methods such as probabilistic graphical models, cluster analysis, discriminant analysis, and dimension reduction to uncover patterns from massive data set. Recently, I also work on topics related to robust statistics, non-convex optimization, and data integration from multiple sources. I am looking for motivated students to explore the aforementioned topics. Please send me an email if you are interested! |
Selected Papers: [Google scholar]
Local Uncertainty Sampling for Large-Scale Multi-Class Logistic Regression [arXiv] [link]
Han L, Tan KM, Yang T, and Zhang T (2019)
The Annals of Statistics, in press
Layer-wise Learning Strategy for Nonparametric Tensor Product Smoothing Spline Regression and Graphical Models [link]
Tan KM, Lu J, Zhang T and Liu. H (2019)
Journal of Machine Learning Research, 20(119):1-38
Propagation of Information along the Cortical Hierarchy as a Function of Attention while
Reading and Listening to Stories [link]
Regev M, Simony E, Lee K, Tan KM, Chen J and Hasson U (2019)
Cerebral Cortex, 29(10):4017--4034.
Sparse Generalized Eigenvalue Problem: Optimal Statistical Rates via Truncated Rayleigh Flow [link] [arXiv] [R package rifle]
Tan KM, Wang Z, Liu H and Zhang T (2018)
Journal of the Royal Statistical Society: Series B, 80(5):1057-1086
A Convex Formulation For High-Dimensional Sparse Sliced Inverse Regression [link] [arXiv] [code]
Tan KM, Wang Z, Zhang T, Liu H and Cook RD (2018)
Biometrika, 105(4):769-782
Local Uncertainty Sampling for Large-Scale Multi-Class Logistic Regression [arXiv] [link]
Han L, Tan KM, Yang T, and Zhang T (2019)
The Annals of Statistics, in press
Layer-wise Learning Strategy for Nonparametric Tensor Product Smoothing Spline Regression and Graphical Models [link]
Tan KM, Lu J, Zhang T and Liu. H (2019)
Journal of Machine Learning Research, 20(119):1-38
Propagation of Information along the Cortical Hierarchy as a Function of Attention while
Reading and Listening to Stories [link]
Regev M, Simony E, Lee K, Tan KM, Chen J and Hasson U (2019)
Cerebral Cortex, 29(10):4017--4034.
Sparse Generalized Eigenvalue Problem: Optimal Statistical Rates via Truncated Rayleigh Flow [link] [arXiv] [R package rifle]
Tan KM, Wang Z, Liu H and Zhang T (2018)
Journal of the Royal Statistical Society: Series B, 80(5):1057-1086
A Convex Formulation For High-Dimensional Sparse Sliced Inverse Regression [link] [arXiv] [code]
Tan KM, Wang Z, Zhang T, Liu H and Cook RD (2018)
Biometrika, 105(4):769-782