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Large margin vs. large volume in transductive learning
Authors:Ran El-Yaniv  Dmitry Pechyony  Vladimir Vapnik
Institution:(1) Computer Science Department, Technion-Israel Institute of Technology, Haifa, 32000, Israel;(2) NEC Laboratories America, Princeton, NJ 08540, USA
Abstract:We consider a large volume principle for transductive learning that prioritizes the transductive equivalence classes according to the volume they occupy in hypothesis space. We approximate volume maximization using a geometric interpretation of the hypothesis space. The resulting algorithm is defined via a non-convex optimization problem that can still be solved exactly and efficiently. We provide a bound on the test error of the algorithm and compare it to transductive SVM (TSVM) using 31 datasets.
Keywords:Transductive learning  Large margin  Large volume  TSVM  Learning principles
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