Aaditya Ramdas

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	All	Since 2016
Citations	1914	1798
h-index	25	25
i10-index	40	38

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2013201420152016201720182019202020219 17 76 137 210 266 418 640 120

Co-authors

Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Larry WassermanProfessor, Department of Statistics and Machine Learning Department, Carnegie Mellon UniversityVerified email at stat.cmu.edu
Aarti SinghAssociate Professor of Machine Learning Department, Carnegie Mellon UniversityVerified email at cmu.edu
Martin WainwrightProfessor of EECS and Statistics, UC BerkeleyVerified email at berkeley.edu
Rina Foygel BarberUniversity of ChicagoVerified email at uchicago.edu
Barnabas PoczosAssociate professor, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Ryan TibshiraniAssociate Professor of Statistics, and Machine Learning, Carnegie Mellon UniversityVerified email at cmu.edu
Leila WehbeCarnegie Mellon UniversityVerified email at cmu.edu
Emmanuel CandesThe Simons Chair in Mathematics and Statistics, Stanford UniversityVerified email at stanford.edu
Jasjeet SekhonEugene Meyer Professor of Data Science, Political Science, and Statistics, Yale UniversityVerified email at yale.edu
Jon McAuliffeProfessor (Adj.) of Statistics, University of California, BerkeleyVerified email at stat.berkeley.edu
Deanna NeedellProfessor of Mathematics, UCLAVerified email at cmc.edu
arthur grettonGatsby Computational Neuroscience Unit, UCLVerified email at gatsby.ucl.ac.uk
Eugene KatsevichAssistant Professor, Wharton Statistics DepartmentVerified email at wharton.upenn.edu
Sivaraman BalakrishnanCarnegie Mellon UniversityVerified email at stat.cmu.edu
Alessandro RinaldoCarnegie Mellon UniversityVerified email at cmu.edu
Marco CuturiGoogle Brain / CREST-ENSAE.Verified email at google.com
Nicolás García TrillosAssistant Professor, Department of Statistics, University of Wisconsin-MadisonVerified email at wisc.edu
Dino SejdinovicUniversity of OxfordVerified email at stats.ox.ac.uk
Alex SmolaAmazon Web ServicesVerified email at smola.org

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
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	175	2014
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	133	2017
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	108	2015
Algorithms for graph similarity and subgraph matching D Koutra, A Parikh, A Ramdas, J Xiang Technical report, Carnegie Mellon University, 2011	106	2011
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	93	2015
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	93	2015
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	89	2016
Fast and flexible ADMM algorithms for trend filtering A Ramdas, RJ Tibshirani Journal of Computational and Graphical Statistics, 2014	83	2014
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	66	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	62	2016
The p-filter: Multi-layer FDR control for grouped hypotheses RF Barber, A Ramdas Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2016	52	2016
Time-uniform, nonparametric, nonasymptotic confidence sequences SR Howard, A Ramdas, J McAuliffe, J Sekhon The Annals of Statistics, 2021	51	2021
Sequential Nonparametric Testing with the Law of the Iterated Logarithm A Balsubramani, A Ramdas 32nd Conference on Uncertainty in Artificial Intelligence (UAI), 2016	42*	2016
On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives SJ Reddi, A Ramdas, B Póczos, A Singh, L Wasserman 18th International Conference on Artificial Intelligence and Statistics, 772-780, 2015	40*	2015
Online control of the false discovery rate with decaying memory A Ramdas, F Yang, MJ Wainwright, MI Jordan Advances in Neural Information Processing Systems, 2017	39	2017
A framework for Multi-A(rmed)/B(andit) testing with online FDR control F Yang, A Ramdas, KG Jamieson, MJ Wainwright Advances in Neural Information Processing Systems, 5957-5966, 2017	38	2017
A general interactive framework for false discovery rate control under structural constraints L Lei, A Ramdas, W Fithian Biometrika, 2020	36	2020
The limits of distribution-free conditional predictive inference R Foygel Barber, EJ Candès, A Ramdas, RJ Tibshirani Information and Inference: A Journal of the IMA, 2020	36*	2020
Rows versus Columns: Randomized Kaczmarz or Gauss--Seidel for Ridge Regression A Hefny, D Needell, A Ramdas SIAM Journal on Scientific Computing 39 (5), S528-S542, 2017	34*	2017
Predictive inference with the jackknife+ RF Barber, EJ Candes, A Ramdas, RJ Tibshirani The Annals of Statistics, 2021	33	2021

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