In this work we consider the task of relaxing the i.i.d assumption in online pattern recognition (or classification), aiming to make existing learning algorithms applicable to a ...
We describe a new boosting algorithm which generates only smooth distributions which do not assign too much weight to any single example. We show that this new boosting algorithm ...
Systems that learn from examples often create a disjunctive concept definition. Small disjuncts are those disjuncts which cover only a few training examples. The problem with sma...
Empirical evidence shows that in favorable situations semi-supervised learning (SSL) algorithms can capitalize on the abundance of unlabeled training data to improve the performan...
A dynamic classification using the support vector machine (SVM) technique is presented in this paper as a new `incremental' framework for multiple-classifying video stream da...