Large scale online learning (2004)
by
Léon Bottou
,
Yann Le Cun
| Venue: | Advances in Neural Information Processing Systems 16 |
| Citations: | 19 - 2 self |
BibTeX
@INPROCEEDINGS{Bottou04largescale,
author = {Léon Bottou and Yann Le Cun},
title = {Large scale online learning},
booktitle = {Advances in Neural Information Processing Systems 16},
year = {2004},
publisher = {MIT Press}
}
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Abstract
We consider situations where training data is abundant and computing resources are comparatively scarce. We argue that suitably designed online learning algorithms asymptotically outperform any batch learning algorithm. Both theoretical and experimental evidences are presented. 1
Citations
| 763 | Numerical Methods for Unconstrained Optimization and Nonlinear Equations - Dennis - 1983 |
| 215 | Natural gradient works efficiently in learning - Amari - 1998 |
| 29 | Theory of Pattern Recognition [in Russian - Vapnik, Chervonenkis - 1974 |
| 20 | Online algorithms and stochastic approximations - Bottou - 1998 |
| 14 | Adaptive method of realizing natural gradient learning for multilayer perceptrons - Amari, Park, et al. - 2000 |
| 11 | On-line learning for very large data sets - Bottou, Cun |
| 5 | Statistical analysis of learning dynamics - Murata, Amari - 1999 |
| 3 | Stochastic Approximations and Efficient Learning - Bottou, Murata - 2002 |
