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 year = {2014},
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 abstract = {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.},
 bibtype = {inbook},
 author = {Peluffo-Ordóñez, D. H. and Castro-Hoyos, C. and Acosta-Medina, Carlos D. and Castellanos-Domínguez, Germán},
 doi = {10.1007/978-3-319-12568-8_50},
 chapter = {Quadratic Problem Formulation with Linear Constraints for Normalized Cut Clustering},
 title = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}
}

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