Abstract. Many supervised machine learning tasks can be cast as multi-class classification problems. Support vector machines (SVMs) excel at binary classification problems, but the...
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
Shape of an object is an important feature for image and multimedia similarity retrievals. In our previous studies we introduced a new boundary-based technique (MBC-based) for shap...
This paper presents a strategy to improve the AdaBoost algorithm with a quadratic combination of base classifiers. We observe that learning this combination is necessary to get be...
Given the pervasive nature of malicious mobile code (viruses, worms, etc.), developing statistical/structural models of code execution is of considerable importance. We investigat...
Geoffrey Mazeroff, Jens Gregor, Michael G. Thomaso...