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ICDM
2003
IEEE

An Algorithm for the Exact Computation of the Centroid of Higher Dimensional Polyhedra and its Application to Kernel Machines

14 years 4 months ago
An Algorithm for the Exact Computation of the Centroid of Higher Dimensional Polyhedra and its Application to Kernel Machines
The Support Vector Machine (SVM) solution corresponds to the centre of the largest sphere inscribed in version space. Alternative approaches like Bayesian Point Machines (BPM) and Analytic Centre Machines have suggested that the generalization performance can be further enhanced by considering other possible centres of version space like the centroid (centre of mass) or the analytic centre. We present an algorithm to compute exactly the centroid of higher dimensional polyhedra, then derive approximation algorithms to build a new learning machine whose performance is comparable to BPM. We also show that for regular kernel matrices (Gaussian kernels for example), the SVM solution can be obtained by solving a linear system of equalities.
Frédéric Maire
Added 04 Jul 2010
Updated 04 Jul 2010
Type Conference
Year 2003
Where ICDM
Authors Frédéric Maire
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