Abstract
The smallest positive eigenvalue of the Laplacian of a network is called the spectral gap and characterizes various dynamics on networks. We propose mathematical programming methods to maximize the spectral gap of a given network by removing a fixed number of nodes. We formulate relaxed versions of the original problem using semidefinite programming and apply them to example networks.
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Masuda, N., Fujie, T., Murota, K. (2013). Application of Semidefinite Programming to Maximize the Spectral Gap Produced by Node Removal. In: Ghoshal, G., Poncela-Casasnovas, J., Tolksdorf, R. (eds) Complex Networks IV. Studies in Computational Intelligence, vol 476. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36844-8_15
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DOI: https://doi.org/10.1007/978-3-642-36844-8_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36843-1
Online ISBN: 978-3-642-36844-8
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