1106 search results - page 24 / 222 » On regularization algorithms in learning theory |
156
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ESANN
2004
15 years 5 months ago
2004
This paper is based on a new way for determining the regularization trade-off in least squares support vector machines (LS-SVMs) via a mechanism of additive regularization which ha...
126
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NIPS
2004
15 years 5 months ago
2004
We provide a principle for semi-supervised learning based on optimizing the rate of communicating labels for unlabeled points with side information. The side information is expres...
142
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NIPS
2008
15 years 5 months ago
2008
The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning. Despite its farreaching application, there is almost n...
133
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ICML
2004
IEEE
16 years 5 months ago
2004
IEEE
Feature selection is the task of choosing a small set out of a given set of features that capture the relevant properties of the data. In the context of supervised classification ...
120
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ICML
2007
IEEE
16 years 5 months ago
2007
IEEE
The l-bfgs limited-memory quasi-Newton method is the algorithm of choice for optimizing the parameters of large-scale log-linear models with L2 regularization, but it cannot be us...