We study the potential benefits to classification prediction that arise from having access to unlabeled samples. We compare learning in the semi-supervised model to the standard, ...
A typical software architecture design process requires the architects to make various trade-off architecture decisions. The architects need to consider different possibilities and...
This work addresses the problem of software fault diagnosis in complex safety critical software systems. The transient manifestations of software faults represent a challenging is...
Abstract. Distributed moving object database servers are a feasible solution to the scalability problem of centralized database systems. In this paper we propose a distributed inde...
A minimally supervised machine learning framework is described for extracting relations of various complexity. Bootstrapping starts from a small set of n-ary relation instances as...