In this paper we describe a new method to reduce the complexity of support vector machines by reducing the number of necessary support vectors included in their solutions. The red...
We address the problem of tracking points in dense vector fields. Such vector fields may come from computational fluid dynamics simulations, environmental monitoring sensors, o...
Liefei Xu, H. Quynh Dinh, Eugene Zhang, Zhongzang ...
We propose a novel, low-complexity, tracking scheme that uses motion vectors directly from a video coder. We compare our tracking algorithm against ground truth data, and show tha...
Gabriel Takacs, Vijay Chandrasekhar, Bernd Girod, ...
Recent work shows that Support vector machines (SVMs) can be solved efficiently in the primal. This paper follows this line of research and shows how to build sparse support vector...
The decision functions constructed by support vector machines (SVM’s) usually depend only on a subset of the training set—the so-called support vectors. We derive asymptotical...