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Published in:
2014 | OriginalPaper | Chapter
Quadratic Problem Formulation with Linear Constraints for Normalized Cut Clustering
Authors : D. H. Peluffo-Ordóñez, C. Castro-Hoyos, Carlos D. Acosta-Medina, Germán Castellanos-Domínguez
Published in: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Publisher: Springer International Publishing
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This work describes a novel quadratic formulation for solving the normalized cuts-based clustering problem as an alternative to spectral clustering approaches. Such formulation is done by establishing simple and suitable constraints, which are further relaxed in order to write a quadratic functional with linear constraints. As a meaningful result of this work, we accomplish a deterministic solution instead of using a heuristic search. Our method reaches comparable performance against conventional spectral methods, but spending significantly lower processing time.