A major obstacle that decreases the performance of text classifiers is the extremely high dimensionality of text data. To reduce the dimension, a number of approaches based on rou...
Given a classifier trained on relatively few training examples, active learning (AL) consists in ranking a set of unlabeled examples in terms of how informative they would be, if ...
Andrea Esuli, Diego Marcheggiani, Fabrizio Sebasti...
Abstract. Over the years, various research projects have attempted to develop a chess program that learns to play well given little prior knowledge beyond the rules of the game. Ea...
The signal-dependent rank order mean (SD-ROM) ?lter is effective at removing high levels of impulse noise from 2D scalar-valued signals. Excellent results have been presented for ...
This paper describes a method of supervised learning based on forward selection branching. This method improves fault tolerance by means of combining information related to general...