3 papers
stat.ME2025
Differentially Private Conformal Prediction via Quantile Binary Search
Ogonnaya M. Romanus, Roberto Molinari
Most Differentially Private (DP) approaches focus on limiting privacy leakage from learners based on the data that they are trained on, there are fewer approaches that consider lea…
stat.ME2025
Fiducial Matching: Differentially Private Inference for Categorical Data
Ogonnaya Michael Romanus, Younes Boulaguiem, Roberto Molinari
The task of statistical inference, which includes the building of confidence intervals and tests for parameters and effects of interest to a researcher, is still an open area of in…
stat.ME2024
Inference for Large Scale Regression Models with Dependent Errors
Lionel Voirol, Haotian Xu, Yuming Zhang +3
The exponential growth in data sizes and storage costs has brought considerable challenges to the data science community, requiring solutions to run learning methods on such data.…