Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
Detection of web attacks is an important issue in current defense-in-depth security framework. In this paper, we propose a novel general framework for adaptive and online detectio...
Wei Wang 0012, Florent Masseglia, Thomas Guyet, Re...
Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant Colony Optimization (ACO) is one such algorithm based on s...
Winner-Takes-All (WTA) prescriptions for Learning Vector Quantization (LVQ) are studied in the framework of a model situation: Two competing prototype vectors are updated accordin...
This paper presents a robust object tracking method via a spatial bias appearance model learned dynamically in video. Motivated by the attention shifting among local regions of a ...