The problem of obtaining the maximum a posteriori estimate of a general discrete random field (i.e. a random field defined using a finite and discrete set of labels) is known ...
Pawan Mudigonda, Vladimir Kolmogorov, Philip H. S....
Abstract. Learning in the context of constraint solving is a technique by which previously unknown constraints are uncovered during search and used to speed up subsequent search. R...
Ian P. Gent, Christopher Jefferson, Lars Kotthoff,...
Deformation at contacts between the workpiece and locators/clamps resulting from large contact forces causes overall workpiece displacement, and affects the localization accuracy o...
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
The problem of monitoring a multivariate linear regression model is relevant in studying the evolving relationship between a set of input variables (features) and one or more depe...