Los puntos clave no están disponibles para este artículo en este momento.
We discuss how the runtime of SVM optimization should decrease as the size of the training data increases. We present theoretical and empirical results demonstrating how a simple subgradient descent approach indeed displays such behavior, at least for linear kernels.
Shalev‐Shwartz et al. (Tue,) studied this question.