Ryan Tibshirani
Ryan Tibshirani
Professor of Statistics
Verified email at - Homepage
Cited by
Cited by
The solution path of the generalized lasso
RJ Tibshirani, J Taylor
Annals of Statistics 39 (3), 1335-1371, 2011
A significance test for the lasso
R Lockhart, J Taylor, RJ Tibshirani, R Tibshirani
Annals of Statistics 42 (2), 413-468, 2014
Strong rules for discarding predictors in lasso‐type problems
R Tibshirani, J Bien, J Friedman, T Hastie, N Simon, J Taylor, ...
Journal of the Royal Statistical Society: Series B 74 (2), 245-266, 2012
The lasso problem and uniqueness
RJ Tibshirani
Electronic Journal of Statistics 7, 1456-1490, 2013
Surprises in high-dimensional ridgeless least squares interpolation
T Hastie, A Montanari, S Rosset, RJ Tibshirani
Annals of Statistics 50 (2), 949-986, 2022
Exact post-selection inference for sequential regression procedures
RJ Tibshirani, J Taylor, R Lockhart, R Tibshirani
Journal of the American Statistical Association 111 (514), 600-620, 2016
Distribution-free predictive inference for regression
J Lei, M G’Sell, A Rinaldo, RJ Tibshirani, L Wasserman
Journal of the American Statistical Association 113 (523), 1094-1111, 2018
Degrees of freedom in lasso problems
RJ Tibshirani, J Taylor
Annals of Statistics 40 (2), 1198-1232, 2012
Adaptive piecewise polynomial estimation via trend filtering
RJ Tibshirani
Annals of Statistics 42 (1), 285-323, 2014
Best subset, forward stepwise or lasso? Analysis and recommendations based on extensive comparisons
T Hastie, R Tibshirani, R Tibshirani
Trend filtering on graphs
YX Wang, J Sharpnack, AJ Smola, RJ Tibshirani
Journal of Machine Learning Research 17 (105), 1-41, 2016
Predictive inference with the jackknife+
RF Barber, EJ Candes, A Ramdas, RJ Tibshirani
Annals of Statistics 49 (1), 486-507, 2021
Conformal prediction under covariate shift
RJ Tibshirani, R Foygel Barber, E Candes, A Ramdas
Advances in neural information processing systems 32, 2019
An open challenge to advance probabilistic forecasting for dengue epidemics
MA Johansson, KM Apfeldorf, S Dobson, J Devita, AL Buczak, B Baugher, ...
Proceedings of the National Academy of Sciences 116 (48), 24268-24274, 2019
Flexible modeling of epidemics with an empirical Bayes framework
LC Brooks, DC Farrow, S Hyun, RJ Tibshirani, R Rosenfeld
PLOS Computational Biology 11 (8), e1004382, 2015
Nearly-isotonic regression
RJ Tibshirani, H Hoefling, R Tibshirani
Technometrics 53 (1), 54-61, 2011
A bias correction for the minimum error rate in cross-validation
RJ Tibshirani, R Tibshirani
Annals of Applied Statistics 3 (2), 822-829, 2009
Fast and flexible ADMM algorithms for trend filtering
A Ramdas, RJ Tibshirani
Journal of Computational and Graphical Statistics 25 (3), 839-858, 2016
The limits of distribution-free conditional predictive inference
R Foygel Barber, EJ Candes, A Ramdas, RJ Tibshirani
Information and Inference: A Journal of the IMA 10 (2), 455-482, 2021
Nonparametric modal regression
YC Chen, CR Genovese, RJ Tibshirani, L Wasserman
Annals of Statistics 44 (2), 489-514, 2016
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