BAYESIAN NONPARAMETRICS

STA 941

Modern nonparametric approaches to statistical analysis. Infinite dimensional Bayesian models: data analysis, inference and prediction. Models of curves, surfaces, probability distributions, partitions and latent feature spaces; nonparametric density estimation, regression and classification; hierarchical, multivariate and functional data analysis models; theory of estimation in function spaces. Methodology of probabilistic process models: Dirichlet, Gaussian, basis/kernel expansion, splines, wavelets, support vector machines and other local regression models. Interfaces of Bayesian:non-Bayesian methods and additional methodological topics. Instructor: Dunson, Ma, or Tokdar

Day / Time: 

TuTh 10:05 AM-11:20 AM

Location: 

Old Chem 003

Instructor: 

Tokdar, Surya

Section: 

01