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Cross-validation: what does it estimate and how well does it do it?


Apr 14, 2021
Stephen Bates, Trevor Hastie, Robert Tibshirani


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Feature-weighted elastic net: using "features of features" for better prediction


Jun 02, 2020
J. Kenneth Tay, Nima Aghaeepour, Trevor Hastie, Robert Tibshirani


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Reluctant generalized additive modeling


Jan 13, 2020
J. Kenneth Tay, Robert Tibshirani

* Change of method name, R package now available 

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Reluctant additive modeling


Dec 04, 2019
J. Kenneth Tay, Robert Tibshirani


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A neural network with feature sparsity


Sep 05, 2019
Ismael Lemhadri, Feng Ruan, Robert Tibshirani


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Spectral Overlap and a Comparison of Parameter-Free, Dimensionality Reduction Quality Metrics


Jul 03, 2019
Jonathan Johannemann, Robert Tibshirani


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Principal component-guided sparse regression


Oct 24, 2018
J. Kenneth Tay, Jerome Friedman, Robert Tibshirani

* Update to acknowledgements 

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A comparison of methods for model selection when estimating individual treatment effects


Jun 13, 2018
Alejandro Schuler, Michael Baiocchi, Robert Tibshirani, Nigam Shah


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Synth-Validation: Selecting the Best Causal Inference Method for a Given Dataset


Oct 31, 2017
Alejandro Schuler, Ken Jung, Robert Tibshirani, Trevor Hastie, Nigam Shah


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Some methods for heterogeneous treatment effect estimation in high-dimensions


Jul 01, 2017
Scott Powers, Junyang Qian, Kenneth Jung, Alejandro Schuler, Nigam H. Shah, Trevor Hastie, Robert Tibshirani


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Nuclear penalized multinomial regression with an application to predicting at bat outcomes in baseball


Jun 30, 2017
Scott Powers, Trevor Hastie, Robert Tibshirani


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Sparse canonical correlation analysis


Jun 02, 2017
Xiaotong Suo, Victor Minden, Bradley Nelson, Robert Tibshirani, Michael Saunders


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High-dimensional regression adjustments in randomized experiments


Oct 27, 2016
Stefan Wager, Wenfei Du, Jonathan Taylor, Robert Tibshirani

* To appear in the Proceedings of the National Academy of Sciences. The present draft does not reflect final copyediting by the PNAS staff 

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Selective Sequential Model Selection


Dec 08, 2015
William Fithian, Jonathan Taylor, Robert Tibshirani, Ryan Tibshirani


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An Ordered Lasso and Sparse Time-Lagged Regression


Jun 03, 2014
Xiaotong Suo, Robert Tibshirani

* 15 pages, 6 figures 

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Collaborative Regression


Jan 22, 2014
Samuel M. Gross, Robert Tibshirani

* 13 pages, 4 figures 

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A Component Lasso


Dec 06, 2013
Nadine Hussami, Robert Tibshirani

* 18 pages, 4 figures 

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A lasso for hierarchical interactions


Jun 19, 2013
Jacob Bien, Jonathan Taylor, Robert Tibshirani

* Annals of Statistics 2013, Vol. 41, No. 3, 1111-1141 
* Published in at http://dx.doi.org/10.1214/13-AOS1096 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

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A Permutation Approach to Testing Interactions in Many Dimensions


Jun 27, 2012
Noah Simon, Robert Tibshirani


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Strong rules for discarding predictors in lasso-type problems


Nov 24, 2010
Robert Tibshirani, Jacob Bien, Jerome Friedman, Trevor Hastie, Noah Simon, Jonathan Taylor, Ryan J. Tibshirani

* 5 

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Transposable regularized covariance models with an application to missing data imputation


Nov 09, 2010
Genevera I. Allen, Robert Tibshirani

* Annals of Applied Statistics 2010, Vol. 4, No. 2, 764-790 
* Published in at http://dx.doi.org/10.1214/09-AOAS314 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

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Inference with Transposable Data: Modeling the Effects of Row and Column Correlations


Apr 01, 2010
Genevera I. Allen, Robert Tibshirani


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Classification by Set Cover: The Prototype Vector Machine


Aug 17, 2009
Jacob Bien, Robert Tibshirani

* 24 pages, 11 figures 

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