We apply kernel-based machine learning methods to online learning situations, and look at the related requirement of reducing the complexity of the learnt classifier. Online meth...
The complexity of variability models makes it hard for product line engineers to maintain their consistency over time. Engineers need support to detect and resolve inconsistencies....
Michael Vierhauser, Deepak Dhungana, Wolfgang Heid...
Abstract XML databases, providing structural querying support, are becoming more and more popular. As we know, XML data may change over time and providing an efficient support to q...
In this paper we propose an approach to support dynamic or runtime variability in systems that must adapt dynamically to changing runtime context. The approach is founded on refle...
Nelly Bencomo, Gordon S. Blair, Carlos A. Flores-C...
We study a class of algorithms that speed up the training process of support vector machines (SVMs) by returning an approximate SVM. We focus on algorithms that reduce the size of...