The authors previously proposed a self-organizing Hierarchical Cerebellar Model Articulation Controller (HCMAC) neural network containing a hierarchical GCMAC neural network and a ...
Real-word applications often involve a binary hypothesis testing problem with one of the two hypotheses ill-defined and hard to be characterized precisely by a single measure. In ...
Abstract. This paper presents an approach to automatically subject index fulltext documents with multiple labels based on binary support vector machines (SVM). The aim was to test ...
Machine learning typically involves discovering regularities in a training set, then applying these learned regularities to classify objects in a test set. In this paper we presen...
Abstract. In this paper, we propose a new method for learning to rank. `Ranking SVM' is a method for performing the task. It formulizes the problem as that of binary classific...