Support Vector Machines (SVMs), though accurate, are still difficult to solve large-scale applications, due to the computational and storage requirement. To relieve this problem,...
We examine the ability to exploit the hierarchical structure of Internet addresses in order to endow network agents with predictive capabilities. Specifically, we consider Suppor...
Background: Classification and variable selection play an important role in knowledge discovery in highdimensional data. Although Support Vector Machine (SVM) algorithms are among...
Natalia Becker, Grischa Toedt, Peter Lichter, Axel...
— This paper presents a novel human detection method based on a Bayesian fusion approach using laser range data and camera images. Laser range data analysis groups data points wi...
Support vector machines (SVMs) excel at two-class discriminative learning problems. They often outperform generative classifiers, especially those that use inaccurate generative m...