Aaditya Ramdas

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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
Rina Foygel BarberUniversity of Chicago確認したメールアドレス: uchicago.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC Berkeley確認したメールアドレス: cs.berkeley.edu
Aarti SinghProfessor of Machine Learning Department, Carnegie Mellon University確認したメールアドレス: cmu.edu
Emmanuel CandesThe Simons Chair in Mathematics and Statistics, Stanford University確認したメールアドレス: stanford.edu
Ryan TibshiraniProfessor of Statistics, UC Berkeley確認したメールアドレス: berkeley.edu
Martin WainwrightProfessor, EECS/Mathematics, Massachusetts Institute of Technology確認したメールアドレス: mit.edu
Ruodu WangUniversity of Waterloo確認したメールアドレス: uwaterloo.ca
Chirag GuptaCarnegie Mellon University確認したメールアドレス: cmu.edu
Johannes RufLondon School of Economics確認したメールアドレス: lse.ac.uk
Barnabas PoczosAssociate professor, Carnegie Mellon University確認したメールアドレス: cs.cmu.edu
Alessandro RinaldoThe University of Texas at Austin確認したメールアドレス: austin.utexas.edu
Leila WehbeCarnegie Mellon University確認したメールアドレス: cmu.edu
Eugene KatsevichAssistant Professor, Wharton Statistics Department確認したメールアドレス: wharton.upenn.edu
Zhiwei Steven WuCarnegie Mellon University確認したメールアドレス: andrew.cmu.edu
Wouter M. KoolenCentrum Wiskunde & Informatica; University of Twente確認したメールアドレス: cwi.nl
Jaehyeok ShinGoogle確認したメールアドレス: google.com
Sivaraman BalakrishnanCarnegie Mellon University確認したメールアドレス: stat.cmu.edu
Shubhanshu ShekharUniversity of Michigan確認したメールアドレス: umich.edu
Aleksandr PodkopaevCarnegie Mellon University確認したメールアドレス: cmu.edu

フォロー

Aaditya Ramdas

Associate Professor (with tenure), Carnegie Mellon University

確認したメールアドレス: stat.cmu.edu - ホームページ

Machine Learning Statistics


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
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	575	2017
Conformal prediction under covariate shift RJ Tibshirani, RF Barber, EJ Candès, A Ramdas Advances in Neural Information Processing Systems 32, 2019	474	2019
Predictive inference with the jackknife+ RF Barber, EJ Candes, A Ramdas, RJ Tibshirani The Annals of Statistics, 2021	361	2021
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	345	2014
Time-uniform, nonparametric, nonasymptotic confidence sequences SR Howard, A Ramdas, J McAuliffe, J Sekhon The Annals of Statistics, 2021	322	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	267*	2020
Conformal prediction beyond exchangeability RF Barber, EJ Candes, A Ramdas, RJ Tibshirani The Annals of Statistics 51 (2), 816-845, 2023	261	2023
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	238	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	226	2015
Universal Inference L Wasserman, A Ramdas, S Balakrishnan Proceedings of the National Academy of Sciences, 2020	217	2020
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	210	2015
Estimating means of bounded random variables by betting I Waudby-Smith, A Ramdas Journal of the Royal Statistical Society, Series B (Methodology), with …, 2022	199	2022
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	185	2015
Algorithms for graph similarity and subgraph matching D Koutra, A Parikh, A Ramdas, J Xiang Technical report, Carnegie Mellon University, 2011	168	2011
Time-uniform Chernoff bounds via nonnegative supermartingales SR Howard, A Ramdas, J McAuliffe, J Sekhon Probability Surveys, 2020	154*	2020
Game-theoretic statistics and safe anytime-valid inference A Ramdas, P Grünwald, V Vovk, G Shafer Statistical Science, 2023	153	2023
Fast and flexible ADMM algorithms for trend filtering A Ramdas, RJ Tibshirani Journal of Computational and Graphical Statistics, 2014	153	2014
False discovery rate control with e-values R Wang, A Ramdas Journal of the Royal Statistical Society: Series B, 2022	122	2022
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	120	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	120	2016

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