—Approaches based on conditional independence tests are among the most popular methods for learning graphical models from data. Due to the predominance of Bayesian networks in th...
It is believed that quantum computing will begin to have a practical impact in industry around year 2010. We propose an approach to test generation and fault localization for a wi...
Systems of argumentation or ’computational dialectic’ are emerging as a powerful means of structuring inter-agent communication in multi-agent systems. Individual systems of co...
The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classifier, is formulated as a concave minimiza...
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...