2 citations · 2 across the 9 of their papers we have counts for
6 papers · 1 filter
Non-partitioned e-detectors for nonparametric sequential change detection
Aytijhya Saha, Aaditya Ramdas
We study the problem of sequential change detection over a general class of probability distributions (), where both the pre-change and post-change distributions are un…
Causal Inference with Categorical Unobserved Confounder via Mixture Learning
Aytijhya Saha, Stephen Bates, Devavrat Shah
Unobserved confounding is a fundamental challenge for estimating causal effects. To address unobserved confounding, recent literature has turned to two different approaches -- prox…
Optimal e-variables under constraints
Aytijhya Saha, Aaditya Ramdas
E-variables enable safe and anytime-valid inference, with log-optimal e-variables given by the likelihood ratio of the least favorable distributions (LFDs) when they exist in compo…
Density estimation with atoms, and functional estimation for mixed discrete-continuous data
Aytijhya Saha, Aaditya Ramdas
In classical density (or density-functional) estimation, it is standard to assume that the underlying distribution has a density with respect to the Lebesgue measure. However, when…
Huber-robust likelihood ratio tests for composite nulls and alternatives
Aytijhya Saha, Aaditya Ramdas
We propose an e-value based framework for testing arbitrary composite nulls against composite alternatives, when an fraction of the data can be arbitrarily corrupted. Our tests…
Testing exchangeability by pairwise betting
Aytijhya Saha, Aaditya Ramdas
In this paper, we address the problem of testing exchangeability of a sequence of random variables, . This problem has been studied under the recently popular fram…