Open AccessProceedings Article
Measure Based Regularization
Olivier Bousquet,Olivier Chapelle,Matthias Hein +2 more
- 09 Dec 2003
- Vol. 16, pp 1221-1228
TL;DR: This paper proposes three theoretical methods for taking into account this distribution P(x) for regularization and provides links to existing graph-based semi-supervised learning algorithms.
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Abstract: 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.
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Semi-Supervised Learning on Riemannian Manifolds
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