Purposeful cross-validation: a novel cross-validation strategy for improved surrogate optimizability
Abstract
Parameter selection during the construction of surrogates is often conducted by minimizing the Mean Squared Cross-Validation Error (MSE-CV). Surrogates constructed using MSE are poorly optimized using gradient-based optimizers. Hence, Nelder–Mead like optimizers are often favoured, which is unfortunate as surrogates make analytical gradients freely available and gradient-based optimizers scale better with increasing dimension. To address this...
Paper Details
Title
Purposeful cross-validation: a novel cross-validation strategy for improved surrogate optimizability
Published Date
Aug 31, 2020
Journal
Volume
53
Issue
9
Pages
1558 - 1573
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History