Bayesian network classifiers have been widely used for classification problems. Given a fixed Bayesian network structure, parameters learning can take two different approaches: ge...
Jiang Su, Harry Zhang, Charles X. Ling, Stan Matwi...
Markov Logic Networks (MLNs) combine Markov Networks and first-order logic by attaching weights to firstorder formulas and viewing them as templates for features of Markov Networks...
We investigate a topic at the interface of machine learning and cognitive science. Human active learning, where learners can actively query the world for information, is contraste...
Rui M. Castro, Charles Kalish, Robert Nowak, Ruich...
In this tutorial five key problems are discussed that occur in the area of lifelong learning. For each problem we will look at the possible technological solutions. The five probl...
Intrinsic complexity is used to measure the complexity of learning areas limited by broken-straight lines (called open semi-hulls) and intersections of such areas. Any strategy le...