Aaditya Ramdas 个人学术档案

引用次数

	总计	2019 年至今
引用	6854	6160
h 指数	41	39
i10 指数	107	104

1800

900

450

1350

2014201520162017201820192020202120222023202418 69 121 189 236 374 554 854 1095 1767 1467

开放获取的出版物数量

查看全部

56 篇文章

0 篇文章

可查看的文章

无法查看的文章

根据资助方的强制性开放获取政策

合著作者

Larry WassermanProfessor, Department of Statistics and Machine Learning Department, Carnegie Mellon University在 stat.cmu.edu 的电子邮件经过验证
Rina Foygel BarberUniversity of Chicago在 uchicago.edu 的电子邮件经过验证
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC Berkeley在 cs.berkeley.edu 的电子邮件经过验证
Aarti SinghProfessor of Machine Learning Department, Carnegie Mellon University在 cmu.edu 的电子邮件经过验证
Emmanuel CandesThe Simons Chair in Mathematics and Statistics, Stanford University在 stanford.edu 的电子邮件经过验证
Ryan TibshiraniProfessor of Statistics, UC Berkeley在 berkeley.edu 的电子邮件经过验证
Martin WainwrightProfessor, EECS/Mathematics, Massachusetts Institute of Technology在 mit.edu 的电子邮件经过验证
Chirag GuptaCarnegie Mellon University在 cmu.edu 的电子邮件经过验证
Barnabas PoczosAssociate professor, Carnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
Johannes RufLondon School of Economics在 lse.ac.uk 的电子邮件经过验证
Leila WehbeCarnegie Mellon University在 cmu.edu 的电子邮件经过验证
Alessandro RinaldoThe University of Texas at Austin在 austin.utexas.edu 的电子邮件经过验证
Eugene KatsevichAssistant Professor, Wharton Statistics Department在 wharton.upenn.edu 的电子邮件经过验证
Ruodu WangUniversity of Waterloo在 uwaterloo.ca 的电子邮件经过验证
Jaehyeok ShinGoogle在 google.com 的电子邮件经过验证
Wouter M. KoolenCentrum Wiskunde & Informatica; University of Twente在 cwi.nl 的电子邮件经过验证
Zhiwei Steven WuCarnegie Mellon University在 andrew.cmu.edu 的电子邮件经过验证
Sivaraman BalakrishnanCarnegie Mellon University在 stat.cmu.edu 的电子邮件经过验证
Shubhanshu ShekharCMU在 umich.edu 的电子邮件经过验证
Deanna NeedellProfessor of Mathematics, UCLA在 cmc.edu 的电子邮件经过验证

关注

Aaditya Ramdas

Statistics and Machine Learning, Carnegie Mellon University

在 stat.cmu.edu 的电子邮件经过验证 - 首页

Machine Learning Statistics


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
On Wasserstein Two Sample Testing and Related Families of Nonparametric Tests A Ramdas, N Garcia, M Cuturi Entropy, Special Issue on Statistical Significance and the Logic of …, 2017	480	2017
Conformal prediction under covariate shift RJ Tibshirani, RF Barber, EJ Candès, A Ramdas Advances in Neural Information Processing Systems 32, 2019	356	2019
Simultaneously uncovering the patterns of brain regions involved in different story reading subprocesses L Wehbe, B Murphy, P Talukdar, A Fyshe, A Ramdas, T Mitchell PLOS One, 2014	323	2014
Predictive inference with the jackknife+ RF Barber, EJ Candes, A Ramdas, RJ Tibshirani The Annals of Statistics, 2021	297	2021
Time-uniform, nonparametric, nonasymptotic confidence sequences SR Howard, A Ramdas, J McAuliffe, J Sekhon The Annals of Statistics, 2021	269	2021
The limits of distribution-free conditional predictive inference RF Barber, EJ Candès, A Ramdas, RJ Tibshirani Information and Inference: A Journal of the IMA, 2020	216*	2020
Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy DJ Sutherland, HY Tung, H Strathmann, S De, A Ramdas, A Smola, ... International Conference on Learning Representations (ICLR), 2017, 2016	210	2016
Convergence properties of the randomized extended Gauss-Seidel and Kaczmarz methods A Ma, D Needell, A Ramdas SIAM Journal on Matrix Analysis and Applications, 2015	200	2015
On the decreasing power of kernel and distance based nonparametric hypothesis tests in high dimensions A Ramdas, S Jakkam Reddi, B Póczos, A Singh, L Wasserman 29th AAAI Conference on Artificial Intelligence, 2015	193	2015
Conformal prediction beyond exchangeability RF Barber, EJ Candes, A Ramdas, RJ Tibshirani The Annals of Statistics 51 (2), 816-845, 2023	170	2023
Fast Two-Sample Testing with Analytic Representations of Probability Measures K Chwialkowski, A Ramdas, D Sejdinovic, A Gretton 29th Conference on Neural Information Processing Systems, 2015	167	2015
Algorithms for graph similarity and subgraph matching D Koutra, A Parikh, A Ramdas, J Xiang Technical report, Carnegie Mellon University, 2011	160	2011
Universal Inference L Wasserman, A Ramdas, S Balakrishnan Proceedings of the National Academy of Sciences, 2020	158	2020
Fast and flexible ADMM algorithms for trend filtering A Ramdas, RJ Tibshirani Journal of Computational and Graphical Statistics, 2014	144	2014
Estimating means of bounded random variables by betting I Waudby-Smith, A Ramdas Journal of the Royal Statistical Society, Series B (Methodology), with …, 2022	138	2022
Time-uniform Chernoff bounds via nonnegative supermartingales SR Howard, A Ramdas, J McAuliffe, J Sekhon Probability Surveys, 2020	128*	2020
A unified treatment of multiple testing with prior knowledge using the p-filter A Ramdas, RF Barber, MJ Wainwright, MI Jordan The Annals of Statistics, 2019	108	2019
Asymptotic behavior of -based Laplacian regularization in semi-supervised learning A El Alaoui, X Cheng, A Ramdas, MJ Wainwright, MI Jordan 29th Annual Conference on Learning Theory, 879-906, 2016	107	2016
Nested conformal prediction and quantile out-of-bag ensemble methods C Gupta, AK Kuchibhotla, AK Ramdas Pattern Recognition, Special Issue on Conformal Prediction and Applications, 2021	97	2021
Admissible anytime-valid sequential inference must rely on nonnegative martingales A Ramdas, J Ruf, M Larsson, W Koolen arXiv preprint arXiv:2009.03167, 2020	94	2020

系统目前无法执行此操作，请稍后再试。

文章 1–20

每年引用数

重复的引用

合并的引用

添加合著者合著作者

上传 PDF

关注此作者

引用次数

合著作者

引用