We establish a mistake bound for an ensemble method for classification based on maximizing the entropy of voting weights subject to margin constraints. The bound is the same as a ...
Classifier subset selection (CSS) from a large ensemble is an effective way to design multiple classifier systems (MCSs). Given a validation dataset and a selection criterion, the...
Abstract. We compare two successful discriminative classification algorithms on three databases from the UCI and STATLOG repositories. The two approaches are the log-linear model ...
Daniel Keysers, Roberto Paredes, Enrique Vidal, He...
This paper contains a new convergence analysis for the Lewis and Torczon generalized pattern search (GPS) class of methods for unconstrained and linearly constrained optimization. ...
Current texture analysis methods enable good discrimination but are computationally too expensive for applications which require high frame rates. This occurs because they use red...