Aaditya Ramdas

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Larry WassermanProfessor, Department of Statistics and Machine Learning Department, Carnegie Mellon UniversityEmail verificata su stat.cmu.edu
Rina Foygel BarberUniversity of ChicagoEmail verificata su uchicago.edu
Ryan TibshiraniProfessor of Statistics, UC BerkeleyEmail verificata su berkeley.edu
Emmanuel CandesThe Simons Chair in Mathematics and Statistics, Stanford UniversityEmail verificata su stanford.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyEmail verificata su cs.berkeley.edu
Aarti SinghProfessor of Machine Learning Department, Carnegie Mellon UniversityEmail verificata su cmu.edu
Martin WainwrightProfessor, EECS/Mathematics, Massachusetts Institute of TechnologyEmail verificata su mit.edu
Ruodu WangUniversity of WaterlooEmail verificata su uwaterloo.ca
Chirag GuptaCarnegie Mellon UniversityEmail verificata su cmu.edu
Alessandro RinaldoThe University of Texas at AustinEmail verificata su austin.utexas.edu
Johannes RufLondon School of EconomicsEmail verificata su lse.ac.uk
Barnabas PoczosAssociate professor, Carnegie Mellon UniversityEmail verificata su cs.cmu.edu
Leila WehbeCarnegie Mellon UniversityEmail verificata su cmu.edu
Eugene KatsevichAssistant Professor, Wharton Statistics DepartmentEmail verificata su wharton.upenn.edu
Zhiwei Steven WuCarnegie Mellon UniversityEmail verificata su andrew.cmu.edu
Jaehyeok ShinGoogleEmail verificata su google.com
Shubhanshu ShekharUniversity of MichiganEmail verificata su umich.edu
Sivaraman BalakrishnanCarnegie Mellon UniversityEmail verificata su stat.cmu.edu
Aleksandr PodkopaevCarnegie Mellon UniversityEmail verificata su cmu.edu
Jasjeet SekhonEugene Meyer Professor of Data Science, Political Science, and Statistics, Yale UniversityEmail verificata su yale.edu

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Aaditya Ramdas

Associate Professor (with tenure), Carnegie Mellon University

Email verificata su stat.cmu.edu - Home page

Machine Learning Statistics


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
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	594	2017
Conformal prediction under covariate shift RJ Tibshirani, RF Barber, EJ Candès, A Ramdas Advances in Neural Information Processing Systems 32, 2019	486	2019
Predictive inference with the jackknife+ RF Barber, EJ Candes, A Ramdas, RJ Tibshirani The Annals of Statistics, 2021	372	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	347	2014
Time-uniform, nonparametric, nonasymptotic confidence sequences SR Howard, A Ramdas, J McAuliffe, J Sekhon The Annals of Statistics, 2021	330	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	278*	2020
Conformal prediction beyond exchangeability RF Barber, EJ Candes, A Ramdas, RJ Tibshirani The Annals of Statistics 51 (2), 816-845, 2023	275	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	248	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	228	2015
Universal Inference L Wasserman, A Ramdas, S Balakrishnan Proceedings of the National Academy of Sciences, 2020	224	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	213	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	210	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
Game-theoretic statistics and safe anytime-valid inference A Ramdas, P Grünwald, V Vovk, G Shafer Statistical Science, 2023	174	2023
Algorithms for graph similarity and subgraph matching D Koutra, A Parikh, A Ramdas, J Xiang Technical report, Carnegie Mellon University, 2011	169	2011
Time-uniform Chernoff bounds via nonnegative supermartingales SR Howard, A Ramdas, J McAuliffe, J Sekhon Probability Surveys, 2020	160*	2020
Fast and flexible ADMM algorithms for trend filtering A Ramdas, RJ Tibshirani Journal of Computational and Graphical Statistics, 2014	154	2014
False discovery rate control with e-values R Wang, A Ramdas Journal of the Royal Statistical Society: Series B, 2022	130	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	123	2019
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	120	2021

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