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COLT
2007
Springer

Transductive Rademacher Complexity and Its Applications

14 years 5 months ago
Transductive Rademacher Complexity and Its Applications
We present data-dependent error bounds for transductive learning based on transductive Rademacher complexity. For specific algorithms we provide bounds on their Rademacher complexity based on their “unlabeled-labeled” decomposition. This decomposition technique applies to many current and practical graph-based algorithms. Finally, we present a new PAC-Bayesian bound for mixtures of transductive algorithms based on our Rademacher bounds.
Ran El-Yaniv, Dmitry Pechyony
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where COLT
Authors Ran El-Yaniv, Dmitry Pechyony
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