Genetic Programming offers freedom in the definition of the cost function that is unparalleled among supervised learning algorithms. However, this freedom goes largely unexploited...
The perceptron algorithm, developed mainly in the machine learning literature, is a simple greedy method for finding a feasible solution to a linear program (alternatively, for le...
1 Establishing suitable programming models for pervasive spaces is essential in improving the productivity, enhancing the quality of pervasive systems, and creating an open platfor...
A mathematical programming formulation is proposed to eliminate irrelevant and redundant features for collaborative computer aided diagnosis which requires to detect multiple clin...
A cognitive model of student programmers is presented. The model is based on protocol studies of students writing Pascal programs, and is implemented in a computer simulation prog...