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papers:collobert-weston-bottou-2006 [2006/04/18 15:19] 127.0.0.1 (old revision restored) |
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===== Trading Convexity for Scalability ===== | ===== Trading Convexity for Scalability ===== | ||
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+ | < | ||
+ | </ | ||
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+ | // | ||
+ | Convex learning algorithms, such as Support Vector Machines (SVMs), are | ||
+ | often seen as highly desirable because they offer strong practical | ||
+ | properties and are amenable to theoretical analysis. | ||
+ | we show how non-convexity can provide scalability advantages over | ||
+ | convexity. | ||
+ | (i) faster SVMs where training errors are no longer support vectors, and | ||
+ | (ii) much faster Transductive SVMs. | ||
<box 99% orange> | <box 99% orange> | ||
- | Ronan Collobert, Jason Weston and Léon Bottou: Trading Convexity for Scalability, | + | Ronan Collobert, Jason Weston and Léon Bottou: |
[[http:// | [[http:// | ||
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url = {http:// | url = {http:// | ||
} | } | ||
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+ | ==== Links ==== | ||
+ | |||
+ | * The [[http:// | ||
+ | * Home page of [[http:// | ||
+ | * Home page of [[http:// | ||
+ | * Home page of [[http:// | ||