Mittagsseminar (in cooperation with J. Lengler, A. Steger, and D. Steurer)

Date and Time: Tuesday, February 12, 2008, 12:15 pm

Duration: This information is not available in the database

Location: OAT S15/S16/S17

Speaker: Joachim Giesen (Max-Planck-Institut für Informatik, Saarbrücken)

The solution path of the slab SVM

Given a set of points in a Hilbert space that can be separated from the origin. The slab support vector machine (slab SVM) is an optimization problem that aims at finding a slab (two parallel hyperplanes whose distance---the slab width---is essentially fixed) that encloses the points and is maximally separated from the origin. Extreme cases of the slab SVM include the smallest enclosing ball problem and an interpolation problem that was used (as the slab SVM itself) in surface reconstruction with radial basis functions. Here we show that the path of solutions of the slab SVM, i.e., the solution parameterized by the slab width is piecewise linear and can be computed efficiently for certain natural point sets.

Joint work with Madhusudan Manjunath (MPI), Michael Eigensatz (ETH) and Mark Pauly (ETH).

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