Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
Segmentation involves separating an object from the background. In this work, we propose a novel segmentation method combining image information with prior shape knowledge, within...
Samuel Dambreville, Yogesh Rathi, Allen Tannenbaum
In this paper we propose an alternative interpretation of Bayesian learning based on maximal evidence principle. We establish a notion of local evidence which can be viewed as a c...
Inductive learning of first-order theory based on examples has serious bottleneck in the enormous hypothesis search space needed, making existing learning approaches perform poorl...
There are well-established methods for reducing the number of support vectors in a trained binary support vector machine, often with minimal impact on accuracy. We show how reduce...