2017
Spatial Decompositions for Large Scale SVMs
AISTATS 2017poster
Although support vector machines (SVMs) are theoretically well understood, their underlying optimization problem becomes very expensive if, for example, hundreds of thousands of samples and a non-linear kernel are considered. Several approaches have been proposed in the past to address this serious…