Measure Based Regularization

Part of Advances in Neural Information Processing Systems 16 (NIPS 2003)

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Olivier Bousquet, Olivier Chapelle, Matthias Hein


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.