Choosing an appropriate kernel is one of the key problems in kernel-based methods. Most existing kernel selection methods require that the class labels of the training examples ar...
We investigate four previously unexplored aspects of ensemble selection, a procedure for building ensembles of classifiers. First we test whether adjusting model predictions to p...
Rich Caruana, Art Munson, Alexandru Niculescu-Mizi...
In active learning, a machine learning algorithm is given an unlabeled set of examples U, and is allowed to request labels for a relatively small subset of U to use for training. ...
Abstract. Practical pattern classification and knowledge discovery problems require selecting a useful subset of features from a much larger set to represent the patterns to be cl...
In this paper, we present a novel segmentationinsensitive approach for mining common patterns from 2 images. We develop an algorithm using the Earth Movers Distance (EMD) framewor...