2 papers
cs.LG2026
Amortized Variational Inference for Logistic Regression with Missing Covariates
M. Cherifi, Aude Sportisse, Xujia Zhu +2
Missing covariate data pose a significant challenge to statistical inference and machine learning, particularly for classification tasks like logistic regression. Classical iterati…
stat.ME2025
Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates
Mohamed Cherifi, Xujia Zhu, Mohammed Nabil El Korso +1
Logistic regression is a fundamental and widely used statistical method for modeling binary outcomes based on covariates. However, the presence of missing data, particularly in set…