Aaditya Ramdas

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Larry WassermanProfessor, Department of Statistics and Machine Learning Department, Carnegie Mellon UniversityVerified email at stat.cmu.edu
Rina Foygel BarberUniversity of ChicagoVerified email at uchicago.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Aarti SinghProfessor of Machine Learning Department, Carnegie Mellon UniversityVerified email at cmu.edu
Emmanuel CandesThe Simons Chair in Mathematics and Statistics, Stanford UniversityVerified email at stanford.edu
Ryan TibshiraniProfessor of Statistics, UC BerkeleyVerified email at berkeley.edu
Martin WainwrightProfessor, EECS/Mathematics, Massachusetts Institute of TechnologyVerified email at mit.edu
Chirag GuptaCarnegie Mellon UniversityVerified email at cmu.edu
Barnabas PoczosAssociate professor, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Johannes RufLondon School of EconomicsVerified email at lse.ac.uk
Leila WehbeCarnegie Mellon UniversityVerified email at cmu.edu
Alessandro RinaldoThe University of Texas at AustinVerified email at austin.utexas.edu
Ruodu WangUniversity of WaterlooVerified email at uwaterloo.ca
Eugene KatsevichAssistant Professor, Wharton Statistics DepartmentVerified email at wharton.upenn.edu
Jaehyeok ShinGoogleVerified email at google.com
Wouter M. KoolenCentrum Wiskunde & Informatica; University of TwenteVerified email at cwi.nl
Zhiwei Steven WuCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Sivaraman BalakrishnanCarnegie Mellon UniversityVerified email at stat.cmu.edu
Shubhanshu ShekharUniversity of MichiganVerified email at umich.edu
Deanna NeedellProfessor of Mathematics, UCLAVerified email at cmc.edu

Aaditya Ramdas

Statistics and Machine Learning, Carnegie Mellon University

Verified email at stat.cmu.edu - Homepage

Machine Learning Statistics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
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	508	2017
Conformal prediction under covariate shift RJ Tibshirani, RF Barber, EJ Candès, A Ramdas Advances in Neural Information Processing Systems 32, 2019	376	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	331	2014
Predictive inference with the jackknife+ RF Barber, EJ Candes, A Ramdas, RJ Tibshirani The Annals of Statistics, 2021	310	2021
Time-uniform, nonparametric, nonasymptotic confidence sequences SR Howard, A Ramdas, J McAuliffe, J Sekhon The Annals of Statistics, 2021	278	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	224*	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	215	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	205	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	198	2015
Conformal prediction beyond exchangeability RF Barber, EJ Candes, A Ramdas, RJ Tibshirani The Annals of Statistics 51 (2), 816-845, 2023	182	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	171	2015
Universal Inference L Wasserman, A Ramdas, S Balakrishnan Proceedings of the National Academy of Sciences, 2020	168	2020
Algorithms for graph similarity and subgraph matching D Koutra, A Parikh, A Ramdas, J Xiang Technical report, Carnegie Mellon University, 2011	163	2011
Fast and flexible ADMM algorithms for trend filtering A Ramdas, RJ Tibshirani Journal of Computational and Graphical Statistics, 2014	148	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	146	2022
Time-uniform Chernoff bounds via nonnegative supermartingales SR Howard, A Ramdas, J McAuliffe, J Sekhon Probability Surveys, 2020	134*	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	111	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	111	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	101	2021
Game-theoretic statistics and safe anytime-valid inference A Ramdas, P Grünwald, V Vovk, G Shafer Statistical Science, 2023	99	2023

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