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8

NIPS
2003

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Measure Based Regularization

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Measure Based Regularization

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We address in this paper the question of how the knowledge of the marginal distribution P(x) can be incorporated in a learning algorithm. We suggest three theoretical methods for taking into account this distribution for regularization and provide links to existing graph-based semi-supervised learning algorithms. We also propose practical implementations.

Olivier Bousquet, Olivier Chapelle, Matthias Hein

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Graph-based Semi-supervised Learning | Learning Algorithms | Marginal Distribution | NIPS 2003 | NIPS 2007 |

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Added	31 Oct 2010
Updated	31 Oct 2010
Type	Conference
Year	2003
Where	NIPS
Authors	Olivier Bousquet, Olivier Chapelle, Matthias Hein

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