The problem of simultaneous feature extraction and selection, for classifier design, is considered. A new framework is proposed, based on boosting algorithms that can either 1) s...
We investigate several feature normalization and scaling approaches for use in speaker verification based on support vector machines. We are particularly interested in methods th...
Andreas Stolcke, Sachin S. Kajarekar, Luciana Ferr...
Abstract. Steganalysis consists in classifying documents as steganographied or genuine. This paper presents a methodology for steganalysis based on a set of 193 features with two m...
Yoan Miche, Patrick Bas, Amaury Lendasse, Christia...
Feature selection has proven to be a valuable technique in supervised learning for improving predictive accuracy while reducing the number of attributes considered in a task. We i...
This paper proposes a supervised learning method for detecting a semantic relation between a given pair of named entities, which may be located in different sentences. The method ...