Conditional random fields(CRFs) are a class of undirected graphical models which have been widely used for classifying and labeling sequence data. The training of CRFs is typicall...
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E...
Background: The Smith-Waterman algorithm for local sequence alignment is more sensitive than heuristic methods for database searching, but also more time-consuming. The fastest ap...
Abstract—Recent improvements in high-throughput genotyping technology make possible genome-wide association studies and status prediction (classification) for common complex dis...
In this study of eight outsourcing projects, we seek to understand the mechanisms that companies put in place to coordinate knowledge work across their boundaries. We find that m...
Background: Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of data classification problems. Since the p...