Simple binary patterns have been successfully used for extracting feature representations for visual object classification. In this paper, we present a method to learn a set of d...
The paper proposes a framework for building learning object (LO) content using ontologies. In the previous work on using ontologies to describe LOs, researchers employed ontologies...
Dragan Gasevic, Jelena Jovanovic, Vladan Devedzic,...
The paper presents a new reinforcement learning mechanism for spiking neural networks. The algorithm is derived for networks of stochastic integrate-and-fire neurons, but it can ...
Abstract. There has been growing interest in practice in using unlabeled data together with labeled data in machine learning, and a number of different approaches have been develo...
In this paper we explore the use of several types of structural restrictions within algorithms for learning Bayesian networks. These restrictions may codify expert knowledge in a g...