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DC Field | Value | Language |
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dc.contributor.author | Ghosh, S | - |
dc.contributor.author | Balasubramanian, K | - |
dc.contributor.author | Yang, X | - |
dc.date.accessioned | 2022-04-29T10:29:33Z | - |
dc.date.available | 2022-04-29T10:29:33Z | - |
dc.date.issued | 2022-01-20 | - |
dc.identifier.citation | Ghosh, S., Balasubramanian, K. and Yang, X. (2022) 'Fractal Gaussian Networks: A Sparse Random Graph Model Based on Gaussian Multiplicative Chaos', IEEE Transactions on Information Theory, 68 (5), pp. 3234 - 3252 (19). doi: 10.1109/TIT.2022.3145197. | en_US |
dc.identifier.issn | 0018-9448 | - |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/24515 | - |
dc.description | The accepted article, arXiv:2008.03038v2 [stat.ML] (for this version) is available at: https://doi.org/10.48550/arXiv.2008.03038. An earlier version of this paper was presented in part at the 37th International Conference on Machine Learning (ICML) 2020. | en_US |
dc.description.sponsorship | 10.13039/501100001459-Ministry of Education, Singapore (MOE) (Grant Number: R-146-000-250-133 and R-146-000-312-114); UC Davis’s Center for Data Science and Artificial Intelligence Research (CeDAR) Innovative Data Science Seed Funding Program 10.13039/100000001-NSF (Grant Number: DMS-2053918); 10.13039/501100001866-Fonds Nationalde la Recherche, Luxembourg (FNR) (Grant Number: MISSILe (R-AGR-3410-12-Z)); Luxembourg and Singapore Universities. | en_US |
dc.description.uri | https://arxiv.org/abs/2008.03038 | - |
dc.format.extent | 3234 - 3252 (19) | - |
dc.format.medium | Print-Electronic | - |
dc.language.iso | en_US | en_US |
dc.publisher | IEEE | en_US |
dc.rights | Copyright © 2021 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. | - |
dc.rights.uri | https://www.ieee.org/publications/rights/rights-policies.html | - |
dc.source | arXiv:2008.03038v2 [stat.ML] for this version, https://doi.org/10.48550/arXiv.2008.03038 | - |
dc.source.uri | https://arxiv.org/pdf/2008.03038 | - |
dc.subject | Gaussian multiplicative chaos | en_US |
dc.subject | sparse random graphs | en_US |
dc.subject | generative model | en_US |
dc.subject | fractal networks | en_US |
dc.title | Fractal Gaussian Networks: A Sparse Random Graph Model Based on Gaussian Multiplicative Chaos | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.1109/TIT.2022.3145197 | - |
dc.relation.isPartOf | IEEE Transactions on Information Theory | - |
pubs.issue | 5 | - |
pubs.publication-status | Published | - |
pubs.volume | 68 | - |
dc.identifier.eissn | 1557-9654 | - |
Appears in Collections: | Dept of Mathematics Research Papers |
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FullText.pdf | Copyright © 2021 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. | 3.02 MB | Adobe PDF | View/Open |
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