Bayesian methods outperform classical ones on prediction error in correlated weak-signal settings, with Horseshoe providing near-nominal coverage and Lasso tying Spike-and-Slab on variable selection F1 score.
Regularization and variable selection via the elastic net.Journal of the Royal Statistical Society: Series B (Statistical Methodology), 67(2):301–320
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
ACCEPT 1representative citing papers
citing papers explorer
-
Sparse Regression under Correlation and Weak Signals: A Reproducible Benchmark of Classical and Bayesian Methods
Bayesian methods outperform classical ones on prediction error in correlated weak-signal settings, with Horseshoe providing near-nominal coverage and Lasso tying Spike-and-Slab on variable selection F1 score.