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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/25452
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dc.contributor.authorLai, Y-
dc.contributor.authorGuan, W-
dc.contributor.authorLuo, L-
dc.contributor.authorGuo, Y-
dc.contributor.authorSong, H-
dc.contributor.authorMeng, H-
dc.date.accessioned2022-11-05T12:57:11Z-
dc.date.available2022-11-05T12:57:11Z-
dc.date.issued2022-10-25-
dc.identifierORCID iD: Yuping Lai https://orcid.org/0000-0002-3797-1228-
dc.identifierORCID iD: Wenbo Guan https://orcid.org/0000-0002-4645-6121-
dc.identifierORCID iD: Lijuan Luo https://orcid.org/0000-0002-3702-372X-
dc.identifierORCID iD: Heping Song https://orcid.org/0000-0002-8583-2804-
dc.identifierORCID iD: Hongying Meng https://orcid.org/0000-0002-8836-1382-
dc.identifier.citationLai, Y..et al. (2022) 'Bayesian Estimation of Inverted Beta Mixture Models With Extended Stochastic Variational Inference for Positive Vector Classification', IEEE Transactions on Neural Networks and Learning Systems, 0 (early access), pp. 1 - 15. doi: 10.1109/tnnls.2022.3213518en_US
dc.identifier.issn2162-237X-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/25452-
dc.description.sponsorship10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62272051, 62172193 and 72101157); 10.13039/501100012226-Fundamental Research Funds for the Central Universities (Grant Number: 2022RC16); Research and Development Program of Beijing Municipal Education Commission (Grant Number: KM201910009014).en_US
dc.format.extent1 - 15-
dc.format.mediumPrint-Electronic-
dc.language.isoen_USen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.rightsCopyright © 2022 Institute of Electrical and Electronics Engineers (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. See: https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelines-and-policies/post-publication-policies/-
dc.rights.urihttps://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelines-and-policies/post-publication-policies/-
dc.subjectextended stochastic variational inferenceen_US
dc.subjectmixture modelsen_US
dc.subjectBayesian estimationen_US
dc.subjecttext categrizationen_US
dc.subjectnetwork traffiic classificationen_US
dc.subjectmisuse intrusion detectonen_US
dc.titleBayesian Estimation of Inverted Beta Mixture Models With Extended Stochastic Variational Inference for Positive Vector Classificationen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1109/tnnls.2022.3213518-
dc.relation.isPartOfIEEE Transactions on Neural Networks and Learning Systems-
pubs.publication-statusPublished-
pubs.volume0-
dc.identifier.eissn2162-2388-
dc.rights.holderIEEE-
Appears in Collections:Dept of Electronic and Electrical Engineering Research Papers

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