Aaditya Ramdas
Aaditya Ramdas
Statistics and Machine Learning, Carnegie Mellon University
Adresse e-mail validée de stat.cmu.edu - Page d'accueil
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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
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
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
Algorithms for graph similarity and subgraph matching
D Koutra, A Parikh, A Ramdas, J Xiang
Technical report, Carnegie Mellon University, 2011
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
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
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
Fast and flexible ADMM algorithms for trend filtering
A Ramdas, RJ Tibshirani
Journal of Computational and Graphical Statistics, 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
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
Time-uniform, nonparametric, nonasymptotic confidence sequences
SR Howard, A Ramdas, J McAuliffe, J Sekhon
The Annals of Statistics, 2021
Predictive inference with the jackknife+
RF Barber, EJ Candes, A Ramdas, RJ Tibshirani
The Annals of Statistics, 2021
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
Sequential Nonparametric Testing with the Law of the Iterated Logarithm
A Balsubramani, A Ramdas
32nd Conference on Uncertainty in Artificial Intelligence (UAI), 2016
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
Conformal prediction under covariate shift
AR RJ Tibshirani, RF Barber, EJ Candès
Advances in Neural Information Processing Systems 32, 2019
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
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
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
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
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