184 citations · 815 across the 63 of their papers we have counts for
4 papers · 1 filter
Dynamic Trees for Learning and Design
Matthew A. Taddy, Robert B. Gramacy, Nicholas G. Polson
Dynamic regression trees are an attractive option for automatic regression and classification with complicated response surfaces in on-line application settings. We create a sequen…
Particle learning of Gaussian process models for sequential design and optimization
Robert B. Gramacy, Nicholas G. Polson
We develop a simulation-based method for the online updating of Gaussian process regression and classification models. Our method exploits sequential Monte Carlo to produce a fast…
Shrinkage regression for multivariate inference with missing data, and an application to portfolio balancing
Robert B. Gramacy, Ester Pantaleo
Portfolio balancing requires estimates of covariance between asset returns. Returns data have histories which greatly vary in length, since assets begin public trading at different…
Classification and categorical inputs with treed Gaussian process models
Tamara Broderick, Robert B. Gramacy
Recognizing the successes of treed Gaussian process (TGP) models as an interpretable and thrifty model for nonparametric regression, we seek to extend the model to classification.…