ECML PKDD 2008
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
15 - 19 September 2008, Antwerp, Belgium
Paper abstractLarge Margin vs. Large Volume in TransductiveRan El-Yaniv - Technion - Israel Institute of Technology, IsraelDmitry Pechyony - Technion - Israel Institute of Technology, Israel Vladimir Vapnik - NEC Laboratories America, Inc., USA Session: Semi Supervised Learning Springer Link: http://dx.doi.org/10.1007/978-3-540-87479-9_8 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. |