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20142024
most citedAnytime-Valid Confidence Sequences in an Enterprise A/B Testing Platform

7 citations · 23 across the 17 of their papers we have counts for

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6 papers · 1 filter

math.ST20231 cited

Reducing sequential change detection to sequential estimation

Shubhanshu Shekhar, Aaditya Ramdas

We consider the problem of sequential change detection, where the goal is to design a scheme for detecting any changes in a parameter or functional of the data stream distribut…

math.ST20232 cited

Randomized and Exchangeable Improvements of Markov's, Chebyshev's and Chernoff's Inequalities

Aaditya Ramdas, Tudor Manole

We present simple randomized and exchangeable improvements of Markov's inequality, as well as Chebyshev's inequality and Chernoff bounds. Our variants are never worse and typically…

math.ST20231 cited

Huber-Robust Confidence Sequences

Hongjian Wang, Aaditya Ramdas

Confidence sequences are confidence intervals that can be sequentially tracked, and are valid at arbitrary data-dependent stopping times. This paper presents confidence sequences f…

math.ST20231 cited

Sequential change detection via backward confidence sequences

Shubhanshu Shekhar, Aaditya Ramdas

We present a simple reduction from sequential estimation to sequential changepoint detection (SCD). In short, suppose we are interested in detecting changepoints in some parameter…

math.ST2023

A Sequential Test for Log-Concavity

Aditya Gangrade, Alessandro Rinaldo, Aaditya Ramdas

On observing a sequence of i.i.d.\ data with distribution on , we ask the question of how one can test the null hypothesis that has a log-concave density. Thi…

math.ST20146 cited

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…