Effective problem-solving about complex engineered devices requires device models that are both adequate for the problem and computationally efficient . Producing such models requ...
P. Pandurang Nayak, Leo Joskowicz, Sanjaya Addanki
We present a novel portfolio selection technique, which replaces the traditional maximization of the utility function with a probabilistic approach inspired by statistical physics....
Robert Marschinski, Pietro Rossi, Massimo Tavoni, ...
In this paper we present a method for the selection of training instances based on the classification accuracy of a SVM classifier. The instances consist of feature vectors repres...
Miguel Lopes, Fabien Gouyon, Alessandro Koerich, L...
We present a novel algorithm for multilingual dependency parsing that uses annotations from a diverse set of source languages to parse a new unannotated language. Our motivation i...
Background: Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of n...