In this paper, we present the evolution of adaptive resonance theory (ART) neural network architectures (classifiers) using a multiobjective optimization approach. In particular, w...
Assem Kaylani, Michael Georgiopoulos, Mansooreh Mo...
We present a tool that predicts whether the software under development inside an IDE has a bug. An IDE plugin performs this prediction, using the Change Classification technique t...
We examine the ability to exploit the hierarchical structure of Internet addresses in order to endow network agents with predictive capabilities. Specifically, we consider Suppor...
Most approaches to learn classifiers for structured objects (e.g., images) use generative models in a classical Bayesian framework. However, state-of-the-art classifiers for vecto...
The ability to correctly classify sentences that describe events is an important task for many natural language applications such as Question Answering (QA) and Text Summarisation....