Carvalho boston university

He will show how usual regularization penalties can be cast as prior distributions on regression coefficients under a Bayesian setup, and propose a computationally efficient EM fitting procedure.

For the case study, he will discuss how publicly available data from the city of Boston can be cleaned, visualized, and explored to give valuable insights into model building, calibration, and presentation and interpretation of results.

His main research interests are Bayesian and computational statistics and data science applications in many fields such as engineering, genetics, and social sciences. Fall at the University of Southern Maine.

College of Science, Technology, and Health. Today's Hours October 25, Skip to Main Content Menu. Keywords Search Search. Share This Story:. Research My main research interests are in Bayesian inference for structured, often high-dimensional, discrete spaces, and Computational Statistics. Bayesian Statistics : Statistical inference point and interval estimation on high-dimensional discrete spaces: characterization, algorithms, and applications.

Centroid estimation. Objective Bayes : Variable selection from invariance-based priors. Computational Statistics : MCMC methods in discrete structures and constrained high-dimensional discrete spaces. Graphical models. Computational Biology : Bayesian statistical inference applied to sequence analysis, glyco-proteomics, genome-wide association studies GWAS , and, more generally, systems biology. Networks : Community detection and inference in stochastic blockmodels. Network modeling, regression and regularization.