4 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.LG2018★ 4 cited
Pooling homogeneous ensembles to build heterogeneous ones
Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez
In ensemble methods, the outputs of a collection of diverse classifiers are combined in the expectation that the global prediction be more accurate than the individual ones. Hetero…
cs.LG2016
Vote-boosting ensembles
Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez
Vote-boosting is a sequential ensemble learning method in which the individual classifiers are built on different weighted versions of the training data. To build a new classifier,…