The aim of this paper is to compare Bayesian network classifiers to the k-NN classifier based on a subset of features. This subset is established by means of sequential feature se...
This paper introduces a foundation for inductive learning based on the use of higher-order logic for knowledge representation. In particular, the paper (i) provides a systematic i...
Antony F. Bowers, Christophe G. Giraud-Carrier, Jo...
Abstract--Suppose for a given classification or function approximation (FA) problem data are collected using sensors. From the output of the th sensor, features are extracted, ther...
Recently, many applications for Restricted Boltzmann Machines (RBMs) have been developed for a large variety of learning problems. However, RBMs are usually used as feature extrac...
In this paper, we consider a smoothing kernelbased classification rule and propose an algorithm for optimizing the performance of the rule by learning the bandwidth of the smoothi...
Bharath K. Sriperumbudur, Omer A. Lang, Gert R. G....