Instead of relying completely on machine intelligence in anomaly event analysis and correlation, in this paper, we take one step back and investigate the possibility of a human-int...
Soon Tee Teoh, Kwan-Liu Ma, Shyhtsun Felix Wu, Dan...
Abstract. In this work we investigate several issues in order to improve the performance of probabilistic estimation trees (PETs). First, we derive a new probability smoothing that...
Abstract. Distributed heterogeneous search environments are an emerging phenomenon in Web search, in which topic-specific search engines provide search services, and metasearchers...
Abstract. Tree induction methods and linear models are popular techniques for supervised learning tasks, both for the prediction of nominal classes and continuous numeric values. F...
Abstract. Most of multi-agent reinforcement learning algorithms aim to converge to a Nash equilibrium, but a Nash equilibrium does not necessarily mean a desirable result. On the o...