The statistical perspective on boosting algorithms focuses on optimization, drawing parallels with maximum likelihood estimation for logistic regression. In this paper we present ...
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
Abstract. Internet traffic prediction plays a fundamental role in network design, management, control, and optimization. The self-similar and non-linear nature of network traffic m...
Hanghang Tong, Chongrong Li, Jingrui He, Yang Chen
Gradient Boosting and bagging applied to regressors can reduce the error due to bias and variance respectively. Alternatively, Stochastic Gradient Boosting (SGB) and Iterated Baggi...
Abstract. Smooth boosting algorithms are variants of boosting methods which handle only smooth distributions on the data. They are proved to be noise-tolerant and can be used in th...