In this paper, we compare the (1+1)-CMA-ES to the (1+2s m)CMA-ES, a recently introduced quasi-random (1+2)-CMAES that uses mirroring as derandomization technique as well as a sequ...
Text categorisation relies heavily on feature selection. Both the possible reduction in dimensionality as well as improvements in classification performance are highly desirable. ...
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
The delay fault test pattern set generated by timing unaware commercial ATPG tools mostly affects very short paths, thereby increasing the escape chance of smaller delay defects. ...
Feature selection for unsupervised tasks is particularly challenging, especially when dealing with text data. The increase in online documents and email communication creates a nee...
Nirmalie Wiratunga, Robert Lothian, Stewart Massie