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ICML
2008
IEEE

Large scale manifold transduction

10 years 2 months ago
Large scale manifold transduction
We show how the regularizer of Transductive Support Vector Machines (TSVM) can be trained by stochastic gradient descent for linear models and multi-layer architectures. The resulting methods can be trained online, have vastly superior training and testing speed to existing TSVM algorithms, can encode prior knowledge in the network architecture, and obtain competitive error rates. We then go on to propose a natural generalization of the TSVM loss function that takes into account neighborhood and manifold information directly, unifying the twostage Low Density Separation method into a single criterion, and leading to state-of-theart results.
Michael Karlen, Jason Weston, Ayse Erkan, Ronan Co
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2008
Where ICML
Authors Michael Karlen, Jason Weston, Ayse Erkan, Ronan Collobert
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