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Polyhedral Separability through Successive LP

Academic Article
Publication Date:
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.
Iris type:
01.01 Articolo in rivista
Keywords:
Classification; Separability; Machine learning.; Optimization
List of contributors:
Astorino, Annabella
Authors of the University:
ASTORINO ANNABELLA
Handle:
https://iris.cnr.it/handle/20.500.14243/126520
Published in:
JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
Journal
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