72 citations · 107 across the 5 of their papers we have counts for
7 papers
Online control of the false discovery rate with decaying memory
Aaditya Ramdas, Fanny Yang, Martin J. Wainwright +1
In the online multiple testing problem, p-values corresponding to different null hypotheses are observed one by one, and the decision of whether or not to reject the current hypoth…
A framework for Multi-A(rmed)/B(andit) testing with online FDR control
Fanny Yang, Aaditya Ramdas, Kevin Jamieson +1
We propose an alternative framework to existing setups for controlling false alarms when multiple A/B tests are run over time. This setup arises in many practical applications, e.g…
Optimal Rates and Tradeoffs in Multiple Testing
Maxim Rabinovich, Aaditya Ramdas, Michael I. Jordan +1
Multiple hypothesis testing is a central topic in statistics, but despite abundant work on the false discovery rate (FDR) and the corresponding Type-II error concept known as the f…
Asymptotic behavior of -based Laplacian regularization in semi-supervised learning
Ahmed El Alaoui, Xiang Cheng, Aaditya Ramdas +2
Given a weighted graph with vertices, consider a real-valued regression problem in a semi-supervised setting, where one observes labeled vertices, and the task is to label…
Fast Two-Sample Testing with Analytic Representations of Probability Measures
Kacper Chwialkowski, Aaditya Ramdas, Dino Sejdinovic +1
We propose a class of nonparametric two-sample tests with a cost linear in the sample size. Two tests are given, both based on an ensemble of distances between analytic functions r…
An Analysis of Active Learning With Uniform Feature Noise
Aaditya Ramdas, Barnabas Poczos, Aarti Singh +1
In active learning, the user sequentially chooses values for feature and an oracle returns the corresponding label . In this paper, we consider the effect of feature noise i…