Ryan Tibshirani

引用先

	すべて	2019 年以来
引用	12821	9716
h 指標	49	45
i10 指標	86	82

2300

1150

575

1725

2011201220132014201520162017201820192020202120222023202442 70 138 244 404 504 689 782 954 1282 1720 1875 2294 1574

オープンアクセス

すべて表示

53 件の論文

0 件の論文

利用可能

利用不可

助成機関の要件に基づく

共著者

Robert TibshiraniProfessor of Biomedical Data Sciences, and of Statistics, Stanford University確認したメールアドレス: stanford.edu
Jonathan TaylorProfessor of Statistics, Stanford University確認したメールアドレス: stanford.edu
Trevor HastieProfessor of Statistics, Stanford University確認したメールアドレス: stanford.edu
Larry WassermanProfessor, Department of Statistics and Machine Learning Department, Carnegie Mellon University確認したメールアドレス: stat.cmu.edu
Aaditya RamdasStatistics and Machine Learning, Carnegie Mellon University確認したメールアドレス: stat.cmu.edu
Alessandro RinaldoThe University of Texas at Austin確認したメールアドレス: austin.utexas.edu
Roni RosenfeldProfessor, Carnegie Mellon University確認したメールアドレス: cs.cmu.edu
Richard LockhartProfessor of Statistics, Simon Fraser University確認したメールアドレス: sfu.ca
Emmanuel CandesThe Simons Chair in Mathematics and Statistics, Stanford University確認したメールアドレス: stanford.edu
Sangwon HyunUniversity of California, Santa Cruz確認したメールアドレス: ucsc.edu
Rina Foygel BarberUniversity of Chicago確認したメールアドレス: uchicago.edu
Yu-Xiang WangAssociate Professor @ UC San Diego確認したメールアドレス: ucsd.edu
James SharpnackUC Davis Statistics Department確認したメールアドレス: ucdavis.edu
Veeranjaneyulu SadhanalaGoogle確認したメールアドレス: google.com
Saharon RossetTel Aviv University確認したメールアドレス: post.tau.ac.il
Jacob BienStatistics, University of Southern California確認したメールアドレス: usc.edu
Max G'SellCarnegie Mellon University確認したメールアドレス: cmu.edu
David C. FarrowCarnegie Mellon University確認したメールアドレス: andrew.cmu.edu
Alex SmolaBoson AI確認したメールアドレス: smola.org
Jing LeiCarnegie Mellon University確認したメールアドレス: andrew.cmu.edu

フォロー

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

Statistics Machine Learning


タイトル引用回数順公開年順タイトル順	引用先引用先	年
The solution path of the generalized lasso RJ Tibshirani, J Taylor Annals of Statistics 39 (3), 1335-1371, 2011	1078	2011
A significance test for the lasso R Lockhart, J Taylor, RJ Tibshirani, R Tibshirani Annals of Statistics 42 (2), 413-468, 2014	859	2014
Surprises in high-dimensional ridgeless least squares interpolation T Hastie, A Montanari, S Rosset, RJ Tibshirani Annals of Statistics 50 (2), 949-986, 2022	821	2022
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	798	2018
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	758	2012
The lasso problem and uniqueness RJ Tibshirani Electronic Journal of Statistics 7, 1456-1490, 2013	736	2013
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	616*	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	552*	2016
Adaptive piecewise polynomial estimation via trend filtering RJ Tibshirani Annals of Statistics 42 (1), 285-323, 2014	447	2014
Degrees of freedom in lasso problems RJ Tibshirani, J Taylor Annals of Statistics 40 (2), 1198-1232, 2012	444	2012
Conformal prediction under covariate shift RJ Tibshirani, RF Barber, EJ Candes, A Ramdas Advances in Neural Information Processing Systems, 2019	367	2019
Trend filtering on graphs YX Wang, J Sharpnack, AJ Smola, RJ Tibshirani Journal of Machine Learning Research 17 (105), 1-41, 2016	311	2016
Predictive inference with the jackknife+ RF Barber, EJ Candes, A Ramdas, RJ Tibshirani Annals of Statistics 49 (1), 486-507, 2021	304	2021
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	218	2021
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	202	2022
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	199	2019
Conformal prediction beyond exchangeability RF Barber, EJ Candes, A Ramdas, RJ Tibshirani Annals of Statistics 51 (2), 816-845, 2023	175	2023
Nearly-isotonic regression RJ Tibshirani, H Hoefling, R Tibshirani Technometrics 53 (1), 54-61, 2011	154	2011
Karush-Kuhn-Tucker conditions G Gordon, R Tibshirani Lecture notes, Carnegie Mellon University, 2012	151	2012
Fast and flexible ADMM algorithms for trend filtering A Ramdas, RJ Tibshirani Journal of Computational and Graphical Statistics 25 (3), 839-858, 2016	146	2016

現在システムで処理を実行できません。しばらくしてからもう一度お試しください。

論文 1–20

年間引用数

重複した引用

結合された引用

共著者を追加共著者

フォロー

引用先

共著者