← Search

Imon Banerjee

2 accepted papers

2025

Small Resamples, Sharp Guarantees: Convergence Rates for Resampled Studentized Quantile Estimators

NeurIPS 2025poster

The m-out-of-n bootstrap—proposed by \cite{bickel1992resampling}—approximates the distribution of a statistic by repeatedly drawing $m$ subsamples ($m \ll n$) without replacement from an original sample of size n; it is now routinely used for robust inference with heavy-tailed data, bandwidth select…

Cited by 0SourceScholar
2017

Inferring Generative Model Structure with Static Analysis

NeurIPS 2017poster

Obtaining enough labeled data to robustly train complex discriminative models is a major bottleneck in the machine learning pipeline. A popular solution is combining multiple sources of weak supervision using generative models. The structure of these models affects the quality of the training labels…

Cited by 69SourcePDFScholar