Evolutionary support vector machines (ESVMs) are a novel technique that assimilates the learning engine of the state-of-the-art support vector machines (SVMs) but evolves the coef...
Ruxandra Stoean, Dumitru Dumitrescu, Mike Preuss, ...
We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this ...
Mark Craven, David Page, Jude W. Shavlik, Joseph B...
Background: Synthesis of data from published human genetic association studies is a critical step in the translation of human genome discoveries into health applications. Although...
Wei Yu, Melinda Clyne, Siobhan M. Dolan, Ajay Yesu...
This paper introduces a new algorithm to parse discourse within the framework of Rhetorical Structure Theory (RST). Our method is based on recent advances in the field of statisti...
Semi-supervised support vector machines (S3VMs) are a kind of popular approaches which try to improve learning performance by exploiting unlabeled data. Though S3VMs have been fou...