In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
We briefly overview the most recent improvements we have incorporated to the existent implementations of the TAS methodology, the simplified ∆-tree representation of formulas i...
This paper investigates how the Univariate Marginal Distribution Algorithm (UMDA) behaves in non-stationary environments when engaging in sampling and selection strategies designe...
Two types of combining strategies were evaluated namely combining skin features and combining skin classifiers. Several combining rules were applied where the outputs of the skin ...
Chelsia Amy Doukim, Jamal Ahmad Dargham, Ali Cheki...
In this paper, we consider the following scenario: a set of mobile objects continuously track their positions in a road network and are able to communicate with a central server. ...