Extending Expectation Propagation for Graphical Mo

Description
Extending Expectation Propagation for Graphical Models Yuan (Alan) Qi Joint work with Tom Minka Motivation Graphical models are widely used in real-world applications, such as wireless communications and bioinformatics. Inference techniques on graphical models often sacrifice efficiency for accuracy or sacrifice accuracy for efficiency. Need a method that better balances the trade-off between accuracy and efficiency.

Type: ppt