In the recent years support vector machines (SVMs) have been successfully applied to solve a large number of classification problems. Training an SVM, usually posed as a quadrati...
We consider the problem of boosting the accuracy of weak learning algorithms in the agnostic learning framework of Haussler (1992) and Kearns et al. (1992). Known algorithms for t...
AdaBoost and support vector machines (SVM) algorithms are commonly used in the field of object recognition. As classifiers, their classification performance is sensitive to affect...
We consider the existence of a linear weak learner for boosting algorithms. A weak learner for binary classification problems is required to achieve a weighted empirical error on t...
Greedy search is commonly used in an attempt to generate solutions quickly at the expense of completeness and optimality. In this work, we consider learning sets of weighted actio...