Abstract. Turing machines are playing an increasingly significant role in Computer Science domains such as bioinformatics. Instead of directly formulating a solution to a problem, ...
Selection of an optimal estimator typically relies on either supervised training samples (pairs of measurements and their associated true values), or a prior probability model for...
Many semi-supervised learning algorithms only
deal with binary classification. Their extension to the
multi-class problem is usually obtained by repeatedly
solving a set of bina...
Classification with only one labeled example per class is a challenging problem in machine learning and pattern recognition. While there have been some attempts to address this pr...
In this paper, we borrow the concept of reference direction approach from the multi-criterion decision-making literature and combine it with an EMO procedure to develop an algorit...