We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
An on-line recursive algorithm for training support vector machines, one vector at a time, is presented. Adiabatic increments retain the KuhnTucker conditions on all previously se...
Relevance feedback approaches based on support vector machine (SVM) learning have been applied to significantly improve retrieval performance in content-based image retrieval (CBI...
Based on Information Theory, optimal feature selection should be carried out by searching Markov blankets. In this paper, we formally analyze the current Markov blanket discovery ...
An easily implementable mixed-integer algorithm is proposed that generates a nonlinear kernel support vector machine (SVM) classifier with reduced input space features. A single ...