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===== Large Scale Online Learning ===== | ===== Large Scale Online Learning ===== | ||
+ | // | ||
+ | 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. | ||
<box 99% orange> | <box 99% orange> | ||
- | Léon Bottou and Yann LeCun: Large Scale Online Learning, | + | Léon Bottou and Yann LeCun: |
[[http:// | [[http:// | ||
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</ | </ | ||
- | @inproceedings{bottou-lecun-2004, | + | @incollection{bottou-lecun-2004, |
author = {Bottou, L\' | author = {Bottou, L\' | ||
title = {Large Scale Online Learning}, | title = {Large Scale Online Learning}, | ||
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url = {http:// | url = {http:// | ||
} | } | ||
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+ | ==== Notes ==== | ||
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+ | The ASMB version of this work [[bottou-lecun-2004a|(Bottou and LeCun, 2005)]] contains the complete proof. The NIPS version was written several months after the ASMB. It contains only a proof sketch but reports experimental results. It also offers a better discussion of the previous results obtained by Murata and Amari (1998) which are in fact much more general than I initially realized. Relative to these results, this work contains three contributions: | ||
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