21 citations · 43 across the 10 of their papers we have counts for
11 papers
Optimistic Algorithms for Adaptive Estimation of the Average Treatment Effect
Ojash Neopane, Aaditya Ramdas, Aarti Singh
Estimation and inference for the Average Treatment Effect (ATE) is a cornerstone of causal inference and often serves as the foundation for developing procedures for more complicat…
Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment Effect
Ojash Neopane, Aaditya Ramdas, Aarti Singh
Estimation of the Average Treatment Effect (ATE) is a core problem in causal inference with strong connections to Off-Policy Evaluation in Reinforcement Learning. This paper consid…
Best Arm Identification under Additive Transfer Bandits
Ojash Neopane, Aaditya Ramdas, Aarti Singh
We consider a variant of the best arm identification (BAI) problem in multi-armed bandits (MAB) in which there are two sets of arms (source and target), and the objective is to det…
Classification accuracy as a proxy for two sample testing
Ilmun Kim, Aaditya Ramdas, Aarti Singh +1
When data analysts train a classifier and check if its accuracy is significantly different from chance, they are implicitly performing a two-sample test. We investigate the statist…
Minimax Lower Bounds for Linear Independence Testing
Aaditya Ramdas, David Isenberg, Aarti Singh +1
Linear independence testing is a fundamental information-theoretic and statistical problem that can be posed as follows: given points from a dimen…
Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing
Aaditya Ramdas, Sashank J. Reddi, Barnabas Poczos +2
Nonparametric two sample testing is a decision theoretic problem that involves identifying differences between two random variables without making parametric assumptions about thei…
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…
Algorithmic Connections Between Active Learning and Stochastic Convex Optimization
Aaditya Ramdas, Aarti Singh
Interesting theoretical associations have been established by recent papers between the fields of active learning and stochastic convex optimization due to the common role of feedb…
On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-difference Alternatives
Aaditya Ramdas, Sashank J. Reddi, Barnabas Poczos +2
Nonparametric two sample testing deals with the question of consistently deciding if two distributions are different, given samples from both, without making any parametric assumpt…
On the Decreasing Power of Kernel and Distance based Nonparametric Hypothesis Tests in High Dimensions
Sashank J. Reddi, Aaditya Ramdas, Barnabás Póczos +2
This paper is about two related decision theoretic problems, nonparametric two-sample testing and independence testing. There is a belief that two recently proposed solutions, base…
Optimal rates for first-order stochastic convex optimization under Tsybakov noise condition
Aaditya Ramdas, Aarti Singh
We focus on the problem of minimizing a convex function over a convex set given queries to a stochastic first order oracle. We argue that the complexity of convex minim…