In many applications, such as credit default prediction and medical image recognition, test inputs are available in addition to the labeled training examples. We propose a method ...
Abstract. Discriminative and generative methods provide two distinct approaches to machine learning classification. One advantage of generative approaches is that they naturally mo...
In this paper, a novel automatic image annotation system is proposed, which integrates two sets of support vector machines (SVMs), namely the multiple instance learning (MIL)-base...
In model selection procedures in supervised learning, a model is usually chosen so that the expected test error over all possible test input points is minimized. On the other hand...
The stability of sample based algorithms is a concept commonly used for parameter tuning and validity assessment. In this paper we focus on two well studied algorithms, LSI and PCA...