We address the problem of discriminating between two finite point sets, A and B, in the n-dimensional space by h hyperplanes generating a convex polyhedron. If the intersection of the convex hull of A with B is empty, the two sets can be strictly separated (polyhedral separability). We introduce an error function which is piecewise linear but not convex nor concave and define a descent procedure based on iterative solution of LP descent direction finding subproblems.

Polyhedral Separability through Successive LP

Astorino Annabella;
2002

Abstract

We address the problem of discriminating between two finite point sets, A and B, in the n-dimensional space by h hyperplanes generating a convex polyhedron. If the intersection of the convex hull of A with B is empty, the two sets can be strictly separated (polyhedral separability). We introduce an error function which is piecewise linear but not convex nor concave and define a descent procedure based on iterative solution of LP descent direction finding subproblems.
2002
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
Classification
Separability
Machine learning.
Optimization
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/126520
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