A Flexible Empirical Bayes Approach to Generalized Linear Models, with Applications to Sparse Logistic Regression

arXiv:2601.21217 · stat.ML, cs.LG, stat.CO, stat.ME · Submitted 2026-01-29 · Read on arXiv

stat.ML, cs.LG, stat.CO, stat.ME

Submitted: 2026-01-29

Updated: 2026-08-27

Code: https://github.com/DongyueXie/vebglm-paper

Terminology

• AUC — 34× in this paper · explained in 2 episodes
• Variational Inference — 25× in this paper
• Sparsity — 14× in this paper · explained in 4 episodes
• Objective Function — 9× in this paper · explained in 2 episodes
• Regularization — 6× in this paper · explained in 3 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Benchmark — 5× in this paper · explained in 2 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Unified Framework — 3× in this paper · explained in 5 episodes
• Feature Selection — 2× in this paper · explained in 4 episodes
• Variational Bayes — 2× in this paper · explained in 2 episodes
• Area Under the Curve (AUC) — 1× in this paper · explained in 1 episode
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Inverse Problem — 1× in this paper · explained in 2 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Score Function — 1× in this paper · explained in 4 episodes
• Selection Bias — 1× in this paper · explained in 4 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes
• Variational Empirical Bayes — 1× in this paper

Sources

• yaglm: a Python package for fitting and tuning generalized linear models that supports structured, adaptive and non-convex penalties
• High-Dimensional Bayesian Regularised Regression with the BayesReg Package
• ebnm: An R Package for Solving the Empirical Bayes Normal Means Problem Using a Variety of Prior Families
• Understanding Stochastic Natural Gradient Variational Inference

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