Aaditya Ramdas
Aaditya Ramdas
Statistics & Data Science, and Machine Learning, Carnegie Mellon University
Verified email at stat.cmu.edu - Homepage
TitleCited byYear
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
Fast and flexible ADMM algorithms for trend filtering
A Ramdas, RJ Tibshirani
Journal of Computational and Graphical Statistics, 2014
Algorithms for graph similarity and subgraph matching
D Koutra, A Parikh, A Ramdas, J Xiang
Technical report, Carnegie Mellon University, 2011
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
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
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
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
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
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
The p‐filter: multilayer false discovery rate control for grouped hypotheses
RF Barber, A Ramdas
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2017
Sequential Nonparametric Testing with the Law of the Iterated Logarithm
A Balsubramani, A Ramdas
32nd Conference on Uncertainty in Artificial Intelligence (UAI), 2016
Online control of the false discovery rate with decaying memory
A Ramdas, F Yang, MJ Wainwright, MI Jordan
Advances In Neural Information Processing Systems, 5650-5659, 2017
Optimal rates for stochastic convex optimization under Tsybakov noise condition
A Ramdas, A Singh
30th International Conference on Machine Learning, 2013
Algorithmic connections between active learning and stochastic convex optimization
A Ramdas, A Singh
24th International Conference on Algorithmic Learning Theory, 2013
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
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
STAR: A general interactive framework for FDR control under structural constraints
L Lei, A Ramdas, W Fithian
arXiv preprint arXiv:1710.02776, 2017
Adaptivity and computation-statistics tradeoffs for kernel and distance based high dimensional two sample testing
A Ramdas, SJ Reddi, B Poczos, A Singh, L Wasserman
arXiv preprint arXiv:1508.00655, 2015
The system can't perform the operation now. Try again later.
Articles 1–20