Abstract. We pose the problem of determining the rate of convergence at which AdaBoost minimizes exponential loss. Boosting is the problem of combining many "weak," high-...
Abstract. Oza’s Online Boosting algorithm provides a version of AdaBoost which can be trained in an online way for stationary problems. One perspective is that this enables the p...
Adam Pocock, Paraskevas Yiapanis, Jeremy Singer, M...
In order to understand AdaBoost’s dynamics, especially its ability to maximize margins, we derive an associated simplified nonlinear iterated map and analyze its behavior in lo...
Cynthia Rudin, Ingrid Daubechies, Robert E. Schapi...
Recently, boosting has come to be used widely in object-detection applications because of its impressive performance in both speed and accuracy. However, learning weak classifier...
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...