The Bayesian framework offers a number of techniques for inferring an individual's knowledge state from evidence of mastery of concepts or skills. A typical application where ...
This paper discusses a simple representation of variable-dimensional optimization problems for evolutionary algorithms. Although it was successfully applied to the optimization of ...
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
Humans tend to group together related properties in order to understand complex phenomena. When modeling large problems with limited representational resources, it is important to...
In this paper, we propose a new transductive learning framework for image retrieval, in which images are taken as vertices in a weighted hypergraph and the task of image search is...