This paper proposes a general boosting framework for combining multiple kernel models in the context of both classification and regression problems. Our main approach is built on...
Next to prediction accuracy, the interpretability of models is one of the fundamental criteria for machine learning algorithms. While high accuracy learners have intensively been e...
Classic mixture models assume that the prevalence of the various mixture components is fixed and does not vary over time. This presents problems for applications where the goal is...
Xiuyao Song, Chris Jermaine, Sanjay Ranka, John Gu...
This paper presents a hybrid modeling system that fuses LiDAR data, an aerial image and ground view images for rapid creation of accurate building models. Outlines for complex bui...
Object-oriented databases are a recent and important development and many studies of them have been performed. These consider aspects such as data modeling, query languages, perfo...