2 citations · 2 across the 3 of their papers we have counts for
3 papers
stat.ML2025
Evaluation and Optimization of Leave-one-out Cross-validation for the Lasso
Ryan Burn
I develop an algorithm to produce the piecewise quadratic that computes leave-one-out cross-validation for the lasso as a function of its hyperparameter. The algorithm can be used…
stat.ME2023
Deterministic Objective Bayesian Analysis for Spatial Models
Ryan Burn
Berger et al. (2001) and Ren et al. (2012) derived noninformative priors for Gaussian process models of spatially correlated data using the reference prior approach (Berger, Bernar…
stat.ML2020★ 2 cited
Optimizing Approximate Leave-one-out Cross-validation to Tune Hyperparameters
Ryan Burn
For a large class of regularized models, leave-one-out cross-validation can be efficiently estimated with an approximate leave-one-out formula (ALO). We consider the problem of adj…