Aaditya Ramdas

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Larry WassermanProfessor, Department of Statistics and Machine Learning Department, Carnegie Mellon UniversityVerifierad e-postadress på stat.cmu.edu
Rina Foygel BarberUniversity of ChicagoVerifierad e-postadress på uchicago.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerifierad e-postadress på cs.berkeley.edu
Aarti SinghProfessor of Machine Learning Department, Carnegie Mellon UniversityVerifierad e-postadress på cmu.edu
Emmanuel CandesThe Simons Chair in Mathematics and Statistics, Stanford UniversityVerifierad e-postadress på stanford.edu
Ryan TibshiraniProfessor of Statistics, UC BerkeleyVerifierad e-postadress på berkeley.edu
Martin WainwrightProfessor, EECS/Mathematics, Massachusetts Institute of TechnologyVerifierad e-postadress på mit.edu
Ruodu WangUniversity of WaterlooVerifierad e-postadress på uwaterloo.ca
Chirag GuptaCarnegie Mellon UniversityVerifierad e-postadress på cmu.edu
Johannes RufLondon School of EconomicsVerifierad e-postadress på lse.ac.uk
Barnabas PoczosAssociate professor, Carnegie Mellon UniversityVerifierad e-postadress på cs.cmu.edu
Leila WehbeCarnegie Mellon UniversityVerifierad e-postadress på cmu.edu
Alessandro RinaldoThe University of Texas at AustinVerifierad e-postadress på austin.utexas.edu
Eugene KatsevichAssistant Professor, Wharton Statistics DepartmentVerifierad e-postadress på wharton.upenn.edu
Wouter M. KoolenCentrum Wiskunde & Informatica; University of TwenteVerifierad e-postadress på cwi.nl
Jaehyeok ShinGoogleVerifierad e-postadress på google.com
Zhiwei Steven WuCarnegie Mellon UniversityVerifierad e-postadress på andrew.cmu.edu
Sivaraman BalakrishnanCarnegie Mellon UniversityVerifierad e-postadress på stat.cmu.edu
Shubhanshu ShekharUniversity of MichiganVerifierad e-postadress på umich.edu
Aleksandr PodkopaevCarnegie Mellon UniversityVerifierad e-postadress på cmu.edu

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Aaditya Ramdas

Associate Professor, Statistics and Machine Learning, Carnegie Mellon University

Verifierad e-postadress på stat.cmu.edu - Startsida

Machine Learning Statistics


Titel Sortera efter citat Sortera efter år Sortera efter titel	Citeras av Citeras av	År
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	548	2017
Conformal prediction under covariate shift RJ Tibshirani, RF Barber, EJ Candès, A Ramdas Advances in Neural Information Processing Systems 32, 2019	434	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	341	2014
Predictive inference with the jackknife+ RF Barber, EJ Candes, A Ramdas, RJ Tibshirani The Annals of Statistics, 2021	338	2021
Time-uniform, nonparametric, nonasymptotic confidence sequences SR Howard, A Ramdas, J McAuliffe, J Sekhon The Annals of Statistics, 2021	307	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	244*	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	230	2016
Conformal prediction beyond exchangeability RF Barber, EJ Candes, A Ramdas, RJ Tibshirani The Annals of Statistics 51 (2), 816-845, 2023	225	2023
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	220	2015
Universal Inference L Wasserman, A Ramdas, S Balakrishnan Proceedings of the National Academy of Sciences, 2020	204	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	204	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	186	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	177	2015
Algorithms for graph similarity and subgraph matching D Koutra, A Parikh, A Ramdas, J Xiang Technical report, Carnegie Mellon University, 2011	167	2011
Fast and flexible ADMM algorithms for trend filtering A Ramdas, RJ Tibshirani Journal of Computational and Graphical Statistics, 2014	151	2014
Time-uniform Chernoff bounds via nonnegative supermartingales SR Howard, A Ramdas, J McAuliffe, J Sekhon Probability Surveys, 2020	146*	2020
Game-theoretic statistics and safe anytime-valid inference A Ramdas, P Grünwald, V Vovk, G Shafer Statistical Science, 2023	140	2023
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	118	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	117	2016
Admissible anytime-valid sequential inference must rely on nonnegative martingales A Ramdas, J Ruf, M Larsson, W Koolen arXiv preprint arXiv:2009.03167, 2020	108	2020

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