Part of Advances in Neural Information Processing Systems 16 (NIPS 2003)
Léon Bottou, Yann Cun
We consider situations where training data is abundant and computing resources are comparatively scarce. We argue that suitably designed on- line learning algorithms asymptotically outperform any batch learning algorithm. Both theoretical and experimental evidences are presented.