Mixtures of Gaussians are a crucial statistical modeling tool at the heart of many challenging applications in computer vision and machine learning. In this paper, we first descri...
The bin packing problem (BPP) is a real-world problem that arises in different industrial applications related to minimization of space or time. The aim of this research is to au...
Abstract. Visual sensitivity is constantly adjusting to the current visual context through processes of adaptation. These adaptive changes strongly affect all perceptual judgments ...
This paper describes a novel application of Statistical Learning Theory (SLT) for motion prediction. SLT provides analytical VC-generalization bounds for model selection; these bo...
Harry Wechsler, Zoran Duric, Fayin Li, Vladimir Ch...
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...