We present efficient support for generalized arrays of parallel data driven objects. Array elements are regular C++ objects, and are scattered across the parallel machine. An indi...
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
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...
This paper presents data selection procedures for support vector machines (SVM). The purpose of data selection is to reduce the dataset by eliminating as many non support vectors ...