5 papers · 1 filter
Formal Bayesian Transfer Learning via the Total Risk Prior
Nathan Wycoff, Ali Arab, Lisa O. Singh
Existing methods for transfer learning struggle to deal with situations where the source datasets are limited and not guaranteed to be well-aligned with the target dataset. A typic…
Proximal Iteration for Nonlinear Adaptive Lasso
Nathan Wycoff, Lisa O. Singh, Ali Arab +1
Augmenting a smooth cost function with an penalty allows analysts to efficiently conduct estimation and variable selection simultaneously in sophisticated models and can b…
Regression Trees Know Calculus
Nathan Wycoff
Regression trees have emerged as a preeminent tool for solving real-world regression problems due to their ability to deal with nonlinearities, interaction effects and sharp discon…
Sensitivity Prewarping for Local Surrogate Modeling
Nathan Wycoff, Mickaël Binois, Robert B. Gramacy
In the continual effort to improve product quality and decrease operations costs, computational modeling is increasingly being deployed to determine feasibility of product designs…
Sequential Learning of Active Subspaces
Nathan Wycoff, Mickael Binois, Stefan M. Wild
In recent years, active subspace methods (ASMs) have become a popular means of performing subspace sensitivity analysis on black-box functions. Naively applied, however, ASMs requi…