Key points are not available for this paper at this time.
Machine learning methods, such as SVM and neural networks, often improve their accuracy by using models with more parameters trained on large numbers of examples. Building such models on a single machine is often impractical because of the large amount of computation required.
Li et al. (Mon,) studied this question.