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stat.ML2023★ 1 cited
Bayes beats Cross Validation: Efficient and Accurate Ridge Regression via Expectation Maximization
Shu Yu Tew, Mario Boley, Daniel F. Schmidt
We present a novel method for tuning the regularization hyper-parameter, , of a ridge regression that is faster to compute than leave-one-out cross-validation (LOOCV) while yiel…
stat.ML2022
Sparse Horseshoe Estimation via Expectation-Maximisation
Shu Yu Tew, Daniel F. Schmidt, Enes Makalic
The horseshoe prior is known to possess many desirable properties for Bayesian estimation of sparse parameter vectors, yet its density function lacks an analytic form. As such, it…