4 papers
On Thompson Sampling and Bilateral Uncertainty in Additive Bayesian Optimization
Nathan Wycoff
In Bayesian Optimization (BO), additive assumptions can mitigate the twin difficulties of modeling and searching a complex function in high dimension. However, common acquisition f…
A Probabilistic Basis for Low-Rank Matrix Learning
Simon Segert, Nathan Wycoff
Low rank inference on matrices is widely conducted by optimizing a cost function augmented with a penalty proportional to the nuclear norm . However, despite t…
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…
Surrogate Active Subspaces for Jump-Discontinuous Functions
Nathan Wycoff
Surrogate modeling and active subspaces have emerged as powerful paradigms in computational science and engineering. Porting such techniques to computational models in the social s…