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Kean Ming Tan
Daniela M Witten

Showing results (11-20 of 57) with videos related to

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Journal of the Royal Statistical Society. Series B, Statistical Methodology|January 20, 2010
Covariance-regularized regression and classification for high-dimensional problemsDaniela M Witten, Robert Tibshirani
The Annals of Applied Statistics|September 17, 2009
TESTING SIGNIFICANCE OF FEATURES BY LASSOED PRINCIPAL COMPONENTSDaniela M Witten, Robert Tibshirani
Journal of the Royal Statistical Society. Series B, Statistical Methodology|February 11, 2012
Penalized classification using Fisher's linear discriminantDaniela M Witten, Robert Tibshirani
Journal of Machine Learning Research : JMLR|January 24, 2024
Selective inference for <math></math>-means clusteringYiqun T Chen, Daniela M Witten
Nucleic Acids Research|January 24, 2012
On the assessment of statistical significance of three-dimensional colocalization of sets of genomic elementsDaniela M Witten, William Stafford Noble
Statistical Applications in Genetics and Molecular Biology|July 4, 2009
Extensions of sparse canonical correlation analysis with applications to genomic dataDaniela M Witten, Robert J Tibshirani
Biometrics|May 16, 2020
Estimating and inferring the maximum degree of stimulus-locked time-varying brain connectivity networksKean Ming Tan, Junwei Lu, Tong Zhang, et al.
Journal of the Royal Statistical Society. Series B, Statistical Methodology|May 13, 2014
The joint graphical lasso for inverse covariance estimation across multiple classesPatrick Danaher, Pei Wang, Daniela M Witten
Biometrika|September 15, 2016
Selection and estimation for mixed graphical modelsShizhe Chen, Daniela M Witten, Ali Shojaie
Biostatistics (Oxford, England)|April 21, 2009
A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysisDaniela M Witten, Robert Tibshirani, Trevor Hastie
Pageof 6

Showing results (11-20 of 57) with videos related to

Sort By:
Pageof 6
Journal of the Royal Statistical Society. Series B, Statistical Methodology|January 20, 2010
Covariance-regularized regression and classification for high-dimensional problemsDaniela M Witten, Robert Tibshirani
The Annals of Applied Statistics|September 17, 2009
TESTING SIGNIFICANCE OF FEATURES BY LASSOED PRINCIPAL COMPONENTSDaniela M Witten, Robert Tibshirani
Journal of the Royal Statistical Society. Series B, Statistical Methodology|February 11, 2012
Penalized classification using Fisher's linear discriminantDaniela M Witten, Robert Tibshirani
Journal of Machine Learning Research : JMLR|January 24, 2024
Selective inference for <math></math>-means clusteringYiqun T Chen, Daniela M Witten
Nucleic Acids Research|January 24, 2012
On the assessment of statistical significance of three-dimensional colocalization of sets of genomic elementsDaniela M Witten, William Stafford Noble
Statistical Applications in Genetics and Molecular Biology|July 4, 2009
Extensions of sparse canonical correlation analysis with applications to genomic dataDaniela M Witten, Robert J Tibshirani
Biometrics|May 16, 2020
Estimating and inferring the maximum degree of stimulus-locked time-varying brain connectivity networksKean Ming Tan, Junwei Lu, Tong Zhang, et al.
Journal of the Royal Statistical Society. Series B, Statistical Methodology|May 13, 2014
The joint graphical lasso for inverse covariance estimation across multiple classesPatrick Danaher, Pei Wang, Daniela M Witten
Biometrika|September 15, 2016
Selection and estimation for mixed graphical modelsShizhe Chen, Daniela M Witten, Ali Shojaie
Biostatistics (Oxford, England)|April 21, 2009
A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysisDaniela M Witten, Robert Tibshirani, Trevor Hastie
Pageof 6