collaborators

5 papers

stat.ME2026

Extended rank regression for all ordinal data

Peter Hoff, Supratik Basu

The accuracy of inference from a regression model depends largely on how well the model represents the relationship between the mean and variance of the outcomes. As this relations…

math.ST2026

Characterization of Generalized Alpha-Beta Divergence and Associated Entropy Measures

Subhrajyoty Roy, Supratik Basu, Abhik Ghosh +1

Minimum divergence estimators provide a natural framework for robust (parametric) statistical inference. Useful properties of several such divergence measures, including, the Helli…

math.ST2026

Universally Optimal Robustness-Efficiency Tradeoffs for a General Class of Minimum Divergence Estimators

Subhrajyoty Roy, Supratik Basu, Abhik Ghosh +1

Balancing the efficiency of an estimator under ideal conditions against its robustness under contamination remains a central challenge in robust statistics. While minimum divergenc…

math.PR2025

Maximal Inequalities for Independent Random Vectors

Supratik Basu, Arun K Kuchibhotla

Maximal inequalities refer to bounds on expected values of the supremum of averages of random variables over a collection. They play a crucial role in the study of non-parametric a…

stat.ML2025

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…