フォロー
Ryan Tibshirani
Ryan Tibshirani
Professor of Statistics, UC Berkeley
確認したメール アドレス: berkeley.edu - ホームページ
タイトル
引用先
引用先
The solution path of the generalized lasso
RJ Tibshirani, J Taylor
Annals of Statistics 39 (3), 1335-1371, 2011
10722011
A significance test for the lasso
R Lockhart, J Taylor, RJ Tibshirani, R Tibshirani
Annals of Statistics 42 (2), 413-468, 2014
8572014
Surprises in high-dimensional ridgeless least squares interpolation
T Hastie, A Montanari, S Rosset, RJ Tibshirani
Annals of Statistics 50 (2), 949-986, 2022
7922022
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
7652018
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
7542012
The lasso problem and uniqueness
RJ Tibshirani
Electronic Journal of Statistics 7, 1456-1490, 2013
7212013
Best subset, forward stepwise or lasso? Analysis and recommendations based on extensive comparisons
T Hastie, R Tibshirani, RJ Tibshirani
Statistical Science 35 (4), 579-592, 2020
636*2020
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
550*2016
Degrees of freedom in lasso problems
RJ Tibshirani, J Taylor
Annals of Statistics 40 (2), 1198-1232, 2012
4432012
Adaptive piecewise polynomial estimation via trend filtering
RJ Tibshirani
Annals of Statistics 42 (1), 285-323, 2014
4422014
Conformal prediction under covariate shift
RJ Tibshirani, RF Barber, EJ Candes, A Ramdas
Advances in Neural Information Processing Systems, 2019
3392019
Trend filtering on graphs
YX Wang, J Sharpnack, AJ Smola, RJ Tibshirani
Journal of Machine Learning Research 17 (105), 1-41, 2016
3062016
Predictive inference with the jackknife+
RF Barber, EJ Candes, A Ramdas, RJ Tibshirani
Annals of Statistics 49 (1), 486-507, 2021
2892021
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
2052021
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
1972019
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States
EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, AJC Rivadeneira, ...
Proceedings of the National Academy of Sciences 119 (15), e2113561119, 2022
1862022
Conformal prediction beyond exchangeability
RF Barber, EJ Candes, A Ramdas, RJ Tibshirani
Annals of Statistics 51 (2), 816-845, 2023
1572023
Nearly-isotonic regression
RJ Tibshirani, H Hoefling, R Tibshirani
Technometrics 53 (1), 54-61, 2011
1532011
Karush-Kuhn-Tucker conditions
G Gordon, R Tibshirani
Optimization 10 (725/36), 725, 2012
1502012
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
1442015
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