This paper proposes a novel approach for directly tuning the gaussian kernel matrix for one class learning. The popular gaussian kernel includes a free parameter, σ, that requires...
Paul F. Evangelista, Mark J. Embrechts, Boleslaw K...
We examine methods for constructing regression ensembles based on a linear program (LP). The ensemble regression function consists of linear combinations of base hypotheses generat...
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
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...
Evolutionary Algorithms (EAs) are well-known optimization approaches to cope with non-linear, complex problems. These population-based algorithms, however, suffer from a general we...
Shahryar Rahnamayan, Hamid R. Tizhoosh, Magdy M. A...