2 citations · 2 across the 9 of their papers we have counts for
10 papers
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…
Distribution-free changepoint localization after sequential change detection
Aytijhya Saha, Aaditya Ramdas
This paper introduces a distribution-free framework for constructing post-detection confidence sets for changepoints after stopping a sequential change detection procedure. It is w…
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…
Post-detection inference for sequential changepoint localization
Aytijhya Saha, Aaditya Ramdas
This paper addresses a fundamental but largely unexplored challenge in sequential changepoint analysis: conducting inference following a detected change. We develop a very general…
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…
Group-Feature (Sensor) Selection With Controlled Redundancy Using Neural Networks
Aytijhya Saha, Nikhil R. Pal
In this paper, we present a novel embedded feature selection method based on a Multi-layer Perceptron (MLP) network and generalize it for group-feature or sensor selection problems…
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…
Robust Classification of High-Dimensional Data using Data-Adaptive Energy Distance
Jyotishka Ray Choudhury, Aytijhya Saha, Sarbojit Roy +1
Classification of high-dimensional low sample size (HDLSS) data poses a challenge in a variety of real-world situations, such as gene expression studies, cancer research, and medic…