Support vector machines (SVMs) excel at two-class discriminative learning problems. They often outperform generative classifiers, especially those that use inaccurate generative m...
In this paper we analyze the application of parallel and sequential evolutionary algorithms (EAs) to the automatic test data generation problem. The problem consists of automatica...
This paper introduces RankOpt, a linear binary classifier which optimises the area under the ROC curve (the AUC). Unlike standard binary classifiers, RankOpt adopts the AUC stat...
In this paper, we describe an approach for automatically generating configurations for complex applications. Automated generation of system co nfigurations is required to allow lar...
Tim Hinrichs, Nathaniel Love, Charles J. Petrie, L...
The problem of elucidating the functional significance of genes is a key challenge of modern science. Solving this problem can lead to fundamental advancements across multiple are...
Alan Shimoide, Ilmi Yoon, Megumi Fuse, Holly C. Be...