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Minimax Optimal Regression over Sobolev Spaces via Laplacian Regularization on Neighborhood Graphs


Jun 03, 2021
Alden Green, Sivaraman Balakrishnan, Ryan J. Tibshirani


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Deep Quantile Aggregation


Mar 16, 2021
Taesup Kim, Rasool Fakoor, Jonas Mueller, Alexander J. Smola, Ryan J. Tibshirani


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The Implicit Regularization of Stochastic Gradient Flow for Least Squares


Mar 17, 2020
Alnur Ali, Edgar Dobriban, Ryan J. Tibshirani


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Modelling High-Dimensional Categorical Data Using Nonconvex Fusion Penalties


Feb 28, 2020
Benjamin G. Stokell, Rajen D. Shah, Ryan J. Tibshirani

* 41 pages, 10 figures 

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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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A Higher-Order Kolmogorov-Smirnov Test


Mar 24, 2019
Veeranjaneyulu Sadhanala, Yu-Xiang Wang, Aaditya Ramdas, Ryan J. Tibshirani

* 18 pages, AISTATS 2019 

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A Continuous-Time View of Early Stopping for Least Squares Regression


Oct 23, 2018
Alnur Ali, J. Zico Kolter, Ryan J. Tibshirani


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Additive Models with Trend Filtering


Apr 28, 2018
Veeranjaneyulu Sadhanala, Ryan J. Tibshirani

* Tighter and clearer theory, new and updated simulations 

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Distribution-Free Predictive Inference For Regression


Mar 08, 2017
Jing Lei, Max G'Sell, Alessandro Rinaldo, Ryan J. Tibshirani, Larry Wasserman

* 50 pages, 7 figures, 3 tables 

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Trend Filtering on Graphs


Jun 04, 2016
Yu-Xiang Wang, James Sharpnack, Alex Smola, Ryan J. Tibshirani

* Journal of Machine Learning Research Volume (2016) Volume 17 Article 15-147 
* A short version appeared in AISTATS'2015 

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Nonparametric modal regression


Mar 30, 2016
Yen-Chi Chen, Christopher R. Genovese, Ryan J. Tibshirani, Larry Wasserman

* Annals of Statistics 2016, Vol. 44, No. 2, 489-514 
* Published at http://dx.doi.org/10.1214/15-AOS1373 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

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Fast and Flexible ADMM Algorithms for Trend Filtering


Aug 29, 2015
Aaditya Ramdas, Ryan J. Tibshirani

* 22 pages, 10 figures; published in Journal of Computational and Graphical Statistics, 2015 

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A General Framework for Fast Stagewise Algorithms


Jun 13, 2015
Ryan J. Tibshirani

* 56 pages, 15 figures 

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High-Dimensional Longitudinal Classification with the Multinomial Fused Lasso


Jan 29, 2015
Samrachana Adhikari, Fabrizio Lecci, James T. Becker, Brian W. Junker, Lewis H. Kuller, Oscar L. Lopez, Ryan J. Tibshirani


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The Falling Factorial Basis and Its Statistical Applications


Oct 27, 2014
Yu-Xiang Wang, Alex Smola, Ryan J. Tibshirani

* Full version for the ICML paper with the same title 

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Adaptive piecewise polynomial estimation via trend filtering


Mar 21, 2014
Ryan J. Tibshirani

* Annals of Statistics 2014, Vol. 42, No. 1, 285-323 
* Published in at http://dx.doi.org/10.1214/13-AOS1189 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

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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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