Contact Information:
School of Statistics University of Minnesota ktan @ umn.edu |
I am currently an assistant professor in the School of Statistics at University of Minnesota. Previously, I was a postdoctoral research associate supervised by Professors 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 Dr. Daniela Witten.
I am interested in developing statistical machine learning methods for analyzing high-dimensional data sets arising from genomics, neuroscience, and other areas of biology. 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. For students that are interested in taking STAT 5401 and STAT 5102: please try to get into the waitlist. At this time, I am unable to provide permission code to overwrite the class limit due to the large number of students already in the waitlist. |
Selected Papers: [Google scholar]
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
Distributionally Robust Reduced Rank Regression and Principal Component Analysis in High Dimensions [arXiv] [code]
Tan KM, Sun Q and Witten D (2018)
Transformation of Speech Sequences in Human Sensorimotor Circuits [bioRxiv]
Musch K, Himberger K, Tan KM, Valiante TA, and Honey CJ (2018)
Local Uncertainty Sampling for Large-Scale Multi-Class Logistic Regression [arXiv]
Han L, Tan KM, Yang T, and Zhang T (2018)
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
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 (2018)
Cerebral Cortex, in press
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
Distributionally Robust Reduced Rank Regression and Principal Component Analysis in High Dimensions [arXiv] [code]
Tan KM, Sun Q and Witten D (2018)
Transformation of Speech Sequences in Human Sensorimotor Circuits [bioRxiv]
Musch K, Himberger K, Tan KM, Valiante TA, and Honey CJ (2018)
Local Uncertainty Sampling for Large-Scale Multi-Class Logistic Regression [arXiv]
Han L, Tan KM, Yang T, and Zhang T (2018)
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
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 (2018)
Cerebral Cortex, in press