We study the problem of learning using combinations of machines. In particular we present new theoretical bounds on the generalization performance of voting ensembles of kernel ma...
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Ro...