"Graph Estimation"
Han Liu, Ph.D., Princeton University
November 13, 2012 @ 3:30 p.m. - 4:30 p.m.
Location: 701 Blockley Hall
Biostatistics
Abstract: The graphical model has proven to be a useful abstraction in statistics and machine learning. The starting point is the graph of a distribution. While often the graph is assumed given, we are interested in estimating the graph from data. In this talk we present new nonparametric and semiparametric methods for graph estimation. The performance of these methods is illustrated and compared on several real and simulated examples.
