Anomaly detection has received much attention within the literature as a means of determining, in an unsupervised manner, whether a learning domain has changed in a fundamental way...
A novel automatic image annotation system is proposed, which integrates two sets of SVMs (Support Vector Machines), namely the MIL-based (Multiple Instance Learning) and global-fe...
: The need for demand-driven and scaleable integration of heterogeneous data sources is inherent to the process of genome annotation. In this paper we describe the Gene-EYe archite...
We propose a new framework for supervised machine learning. Our goal is to learn from smaller amounts of supervised training data, by collecting a richer kind of training data: an...
Research augmenting B machines presented at B2007 has demonstrated how fragments of control flow expressed as annotations can be added to associated machine operations, and shown t...