This is a survey of some theoretical results on boosting obtained from an analogous treatment of some regression and classi cation boosting algorithms. Some related papers include...
We give an unified convergence analysis of ensemble learning methods including e.g. AdaBoost, Logistic Regression and the Least-SquareBoost algorithm for regression. These methods...
The state-of-the-art object detection algorithm learns a binary classifier to differentiate the foreground object from the background. Since the detection algorithm exhaustively s...
In this paper we examine ensemble methods for regression that leverage or "boost" base regressors by iteratively calling them on modified samples. The most successful lev...
Boosting is a simple yet powerful modeling technique that is used in many machine learning and data mining related applications. In this paper, we propose a novel scale-space based...