2 citations · 2 across the 5 of their papers we have counts for
6 papers
Assumption-lean logistic regression with missing covariates
Jyotishka Ray Choudhury, Kabir Aladin Verchand, Richard J. Samworth +1
Missing covariates are frequently encountered in supervised learning problems, and classical methods for estimation using such data use carefully chosen imputation schemes for miss…
High-Dimensional Robust Change-Point Detection via Angular Kernel Statistics
Jyotishka Ray Choudhury, Yao Xie
We study nonparametric change-point detection for high-dimensional data in regimes where inference must be performed from small batches of observations. Our primary focus is the hi…
The saddlepoint approximation for averages of conditionally independent random variables
Ziang Niu, Jyotishka Ray Choudhury, Eugene Katsevich
Motivated by the application of saddlepoint approximations to resampling-based statistical tests, we prove that the Lugannani-Rice formula has vanishing relative error when applied…
Saddlepoint approximations for plug-in resampling
Ziang Niu, Zhihan Huang, Jyotishka Ray Choudhury +1
Resampling-based procedures can improve on normal approximations in sparse, large-scale testing problems, but their computational cost can be prohibitive. We recognize that several…
Dirichlet Process-based Robust Clustering using the Median-of-Means Estimator
Supratik Basu, Jyotishka Ray Choudhury, Debolina Paul +1
Clustering stands as one of the most prominent challenges in unsupervised machine learning. Among centroid-based methods, the classic -means algorithm, based on Lloyd's heuristi…
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…