The fitness consequences of aneuploidy are driven by condition-dependent gene effects AB Sunshine, C Payen, GT Ong, I Liachko, KM Tan, MJ Dunham PLoS biology 13 (5), e1002155, 2015 | 109 | 2015 |
Learning graphical models with hubs KM Tan, P London, K Mohan, SI Lee, M Fazel, D Witten arXiv preprint arXiv:1402.7349, 2014 | 109 | 2014 |
Metronomic administration of chlorambucil for treatment of dogs with urinary bladder transitional cell carcinoma DR Schrempp, MO Childress, JC Stewart, TN Leach, KM Tan, AH Abbo, ... Journal of the American Veterinary Medical Association 242 (11), 1534-1538, 2013 | 105 | 2013 |
Clinical trial of vinblastine in dogs with transitional cell carcinoma of the urinary bladder EJ Arnold, MO Childress, LM Fourez, KM Tan, JC Stewart, PL Bonney, ... Journal of Veterinary Internal Medicine 25 (6), 1385-1390, 2011 | 102 | 2011 |
Statistical Properties of Convex Clustering KM Tan, D Witten Electronic Journal of Statistics 9 (2), 2324-2347, 2015 | 99 | 2015 |
Randomized trial of cisplatin versus firocoxib versus cisplatin/firocoxib in dogs with transitional cell carcinoma of the urinary bladder DW Knapp, CJ Henry, WR Widmer, KM Tan, GE Moore, JA Ramos‐Vara, ... Journal of Veterinary Internal Medicine 27 (1), 126-133, 2013 | 94 | 2013 |
The cluster graphical lasso for improved estimation of Gaussian graphical models KM Tan, D Witten, A Shojaie Computational statistics & data analysis 85, 23-36, 2015 | 87 | 2015 |
Smoothed quantile regression with large-scale inference X He, X Pan, KM Tan, WX Zhou Journal of Econometrics 232 (2), 367-388, 2023 | 78 | 2023 |
Propagation of information along the cortical hierarchy as a function of attention while reading and listening to stories M Regev, E Simony, K Lee, KM Tan, J Chen, U Hasson Cerebral Cortex 29 (10), 4017-4034, 2019 | 72 | 2019 |
Sparse biclustering of transposable data KM Tan, DM Witten Journal of Computational and Graphical Statistics 23 (4), 985-1008, 2014 | 69 | 2014 |
Sparse generalized eigenvalue problem: Optimal statistical rates via truncated rayleigh flow KM Tan, Z Wang, H Liu, T Zhang Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2018 | 62 | 2018 |
A convex formulation for high-dimensional sparse sliced inverse regression KM Tan, Z Wang, T Zhang, H Liu, RD Cook Biometrika 105 (4), 769-782, 2018 | 42 | 2018 |
High-dimensional quantile regression: Convolution smoothing and concave regularization KM Tan, L Wang, WX Zhou Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022 | 38 | 2022 |
Laplace approximation in high-dimensional Bayesian regression RF Barber, M Drton, KM Tan Statistical Analysis for High-Dimensional Data: The Abel Symposium 2014, 15-36, 2016 | 37 | 2016 |
Local uncertainty sampling for large-scale multiclass logistic regression L Han, KM Tan, T Yang, T Zhang | 34 | 2020 |
Graphical nonconvex optimization via an adaptive convex relaxation Q Sun, KM Tan, H Liu, T Zhang International Conference on Machine Learning, 4810-4817, 2018 | 26* | 2018 |
Communication-constrained distributed quantile regression with optimal statistical guarantees KM Tan, H Battey, WX Zhou Journal of machine learning research 23 (272), 1-61, 2022 | 23 | 2022 |
Transformation of speech sequences in human sensorimotor circuits K Müsch, K Himberger, KM Tan, TA Valiante, CJ Honey Proceedings of the National Academy of Sciences 117 (6), 3203-3213, 2020 | 21 | 2020 |
Classification of RNA-seq data KM Tan, A Petersen, D Witten Statistical analysis of next generation sequencing data, 219-246, 2014 | 21 | 2014 |
Sparse reduced rank Huber regression in high dimensions KM Tan, Q Sun, D Witten Journal of the American Statistical Association 118 (544), 2383-2393, 2023 | 20* | 2023 |