Jun 20, 2007 · We study the problem of learning kernel machines transductively for structured output variables. Transductive learning can be reduced to ...
Abstract. We study the problem of learning kernel ma- chines transductively for structured output variables. Transductive learning can be re-.
▫ Transductive SVM with structured variables. ◇ Uses information from unlabeled data. ◇ Combinatorial, non-convex optimization problem. ▫ Efficient optimization ...
We study the problem of learning kernel machines transductively for structured output variables. Transductive learning can be reduced to combinatorial ...
In order to scale transductive learning to structured variables, this work transforms the corresponding non-convex, combinatorial, constrained optimization ...
Abstract. We study the problem of learning kernel ma- chines transductively for structured output variables. Transductive learning can be re-.
Jun 25, 2015 · Transductive SVMs, on the other hand, take into account even the unlabeled data points. However, the objective of the Transductive SVM is different than that ...
We study the problem of learning kernel machines transductively for structured output variables. Transductive learning can be reduced to combinatorial ...
Jun 21, 2007 · Transductive Support Vector Machines for. Structured Variables ... 1 Why Semi-Supervised Structured Output SVMs? 2 SO-TSVM – The Model.
Transduc- tive support vector machines (TSVMs) implement the idea of transductive learning by including test points in the computation of the margin.