This paper presents two metrics for the Nearest Neighbor Classifier that share the property of being adapted, i.e. learned, on a set of data. Both metrics can be used for similari...
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Ro...
The evaluation of a large implemented natural language processing system involves more than its application to a common performance task. Such tasks have been used in the message u...
This paper addresses how to quickly recognize a character pattern using a lot of case examples without learning. Here without learning means just finding the most similar example...
An extension of the AdaBoost learning algorithm is proposed and brought to bear on the face detection problem. In each weak classifier selection cycle, the novel totally correctiv...