Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach is to apply machine learning algorithms to ...
Wei Fan, Haixun Wang, Philip S. Yu, Salvatore J. S...
A parallel distributed computational model for reasoning and learning is discussed based on a belief network paradigm. Issues like reasoning and learning for the proposed model ar...
In the 21st century it is becoming increasingly common to work and learn in teams that are globally distributed. Such teams rely heavily on ICT to facilitate communication. There ...
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
A powerful approach to search is to try to learn a distribution of good solutions (in particular of the dependencies between their variables) and use this distribution as a basis ...