Background: Massive text mining of the biological literature holds great promise of relating disparate information and discovering new knowledge. However, disambiguation of gene s...
Bob J. A. Schijvenaars, Barend Mons, Marc Weeber, ...
The Fisher kernel is a generic framework which combines the benefits of generative and discriminative approaches to pattern classification. In this contribution, we propose to a...
High-level test pattern generation is today a widely investigated research topic. The present paper proposes a fully automated, simulation-based ATPG system, to address test patte...
Class membership probability estimates are important for many applications of data mining in which classification outputs are combined with other sources of information for decisi...
Incorporating background knowledge into data mining algorithms is an important but challenging problem. Current approaches in semi-supervised learning require explicit knowledge p...
Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan