A novel entropy-based graph signature from the average mixing matrix

Bai, L., Rossi, L., Cui, Lixin et al. (1 more author) (2016) A novel entropy-based graph signature from the average mixing matrix. In: Davis, L., Bimbo, A. Del and Lovell, B., (eds.) 2016 23rd International Conference on Pattern Recognition (ICPR). IEEE Computer Society Press , Los Alamitos, CA, USA , pp. 1339-1344.

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Copyright, Publisher and Additional Information: ©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords: Eigenvalues and eigenfunctions,Entropy,Kernel,Laplace equations,Pattern recognition,Probability distribution,Quantum computing
Dates:
  • Published: 1 December 2016
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Computer Science (York)
Depositing User: Pure (York)
Date Deposited: 03 May 2017 13:40
Last Modified: 24 Jun 2021 03:06
Published Version: https://doi.org/10.1109/ICPR.2016.7899823
Status: Published
Publisher: IEEE Computer Society Press
Refereed: No
Identification Number: https://doi.org/10.1109/ICPR.2016.7899823

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