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Weighted Low Rank Matrix Approximation and Acceleration


Sep 22, 2021
Elena Tuzhilina, Trevor Hastie


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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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Generalized Matrix Factorization


Oct 06, 2020
Łukasz Kidziński, Francis K. C. Hui, David I. Warton, Trevor Hastie


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Simultaneous Relevance and Diversity: A New Recommendation Inference Approach


Sep 27, 2020
Yifang Liu, Zhentao Xu, Qiyuan An, Yang Yi, Yanzhi Wang, Trevor Hastie

* 9 pages 

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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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Ridge Regularizaton: an Essential Concept in Data Science


May 30, 2020
Trevor Hastie

* 17 pages, 5 figures. This paper was invited by Technometrics to appear in a special section to celebrate the 50th anniversary of the 1970 original ridge paper by Hoerl and Kennard 

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Surprises in High-Dimensional Ridgeless Least Squares Interpolation


Apr 02, 2019
Trevor Hastie, Andrea Montanari, Saharon Rosset, Ryan J. Tibshirani

* 43 pages; 12 pdf figures 

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Longitudinal data analysis using matrix completion


Sep 24, 2018
Łukasz Kidziński, Trevor Hastie


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Saturating Splines and Feature Selection


Dec 04, 2017
Nicholas Boyd, Trevor Hastie, Stephen Boyd, Benjamin Recht, Michael Jordan

* Adding missing references and related work 

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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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Telugu OCR Framework using Deep Learning


Feb 15, 2017
Rakesh Achanta, Trevor Hastie


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Sparse Quadratic Discriminant Analysis and Community Bayes


Oct 19, 2016
Ya Le, Trevor Hastie

* Revised version (adding more experiments) 

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Generalized Additive Model Selection


Jun 17, 2015
Alexandra Chouldechova, Trevor Hastie

* 23 pages, 10 figures 

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Matrix Completion and Low-Rank SVD via Fast Alternating Least Squares


Oct 09, 2014
Trevor Hastie, Rahul Mazumder, Jason Lee, Reza Zadeh


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Local case-control sampling: Efficient subsampling in imbalanced data sets


Sep 23, 2014
William Fithian, Trevor Hastie

* Annals of Statistics 2014, Vol. 42, No. 5, 1693-1724 
* Published in at http://dx.doi.org/10.1214/14-AOS1220 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

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Confidence Intervals for Random Forests: The Jackknife and the Infinitesimal Jackknife


Mar 29, 2014
Stefan Wager, Trevor Hastie, Bradley Efron

* To appear in Journal of Machine Learning Research (JMLR) 

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A Blockwise Descent Algorithm for Group-penalized Multiresponse and Multinomial Regression


Nov 26, 2013
Noah Simon, Jerome Friedman, Trevor Hastie


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The Graphical Lasso: New Insights and Alternatives


Aug 07, 2012
Rahul Mazumder, Trevor Hastie

* This is a revised version of our previous manuscript with the same name ArXiv id: http://arxiv.org/abs/1111.5479 

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Exact covariance thresholding into connected components for large-scale Graphical Lasso


Sep 15, 2011
Rahul Mazumder, Trevor Hastie

* Report Version 2 (adding more experiments and correcting minor typos) 

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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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Regularization methods for learning incomplete matrices


Jun 11, 2009
Rahul Mazumder, Trevor Hastie, Rob Tibshirani

* 10 pages, 1 figure 

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