This paper proposes the use of neural network ensembles to boost the performance of a neural network based surface reconstruction algorithm. Ensemble is a very popular and powerfu...
Ioannis P. Ivrissimtzis, Yunjin Lee, Seungyong Lee...
This multidisciplinary study focuses on the application and comparison of several topology preserving mapping models upgraded with some classifier ensemble and boosting techniques ...
Bruno Baruque, Emilio Corchado, Hujun Yin, Jordi R...
A boosting algorithm based on cellular genetic programming to build an ensemble of predictors is proposed. The method evolves a population of trees for a fixed number of rounds an...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
We present a learning framework for structured support vector models in which boosting and bagging methods are used to construct ensemble models. We also propose a selection metho...
We devise a boosting approach to classification and regression based on column generation using a mixture of kernels. Traditional kernel methods construct models based on a single...