—This paper presents a novel approach for automatic recognition of human activities from video sequences. We first group features with high correlations into Category Feature Vec...
In discretization of a continuous variable its numerical value range is divided into a few intervals that are used in classification. For example, Na¨ıve Bayes can benefit from...
Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
—We review the principles of Minimum Description Length and Stochastic Complexity as used in data compression and statistical modeling. Stochastic complexity is formulated as the...