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ICML
2007
IEEE

Transductive support vector machines for structured variables

9 years 12 months ago
Transductive support vector machines for structured variables
We study the problem of learning kernel machines transductively for structured output variables. Transductive learning can be reduced to combinatorial optimization problems over all possible labelings of the unlabeled data. In order to scale transductive learning to structured variables, we transform the corresponding non-convex, combinatorial, constrained optimization problems into continuous, unconstrained optimization problems. The discrete optimization parameters are eliminated and the resulting differentiable problems can be optimized efficiently. We study the effectiveness of the generalized TSVM on multiclass classification and labelsequence learning problems empirically.
Alexander Zien, Ulf Brefeld, Tobias Scheffer
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2007
Where ICML
Authors Alexander Zien, Ulf Brefeld, Tobias Scheffer
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