We introduce a new algorithm for binary classification in the selective sampling protocol. Our algorithm uses Regularized Least Squares (RLS) as base classifier, and for this reas...
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
A challenging issue facing Grid communities is that while Grids can provide access to many heterogeneous resources, the resources to which access is provided often do not match th...
Ian T. Foster, Timothy Freeman, Katarzyna Keahey, ...
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
Human superiority over computers in identifying natural objects like clouds, water, grass etc. comes from two capabilities: the capability to maintain a growing knowledge base per...