Analytic solution and stationary phase approximation for the Bayesian lasso and elastic net
–Neural Information Processing Systems
The lasso and elastic net linear regression models impose a double-exponential prior distribution on the model parameters to achieve regression shrinkage and variable selection, allowing the inference of robust models from large data sets.
Neural Information Processing Systems
Feb-12-2026, 03:03:12 GMT