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...
We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
We describe a new approach for creating concise high-level generative models from range images or other approximate representations of real objects. Using data from a variety of a...
Declarative models play an important role in most software design activities, by allowing designs to be constructed that selectively abstract over complex implementation details. ...
Paulo Pinheiro da Silva, Tony Griffiths, Norman W....
Increasingly, high-assurance applications rely on autonomic systems to respond to changes in their environment. The inherent uncertainty present in the environment of autonomic sy...