Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/25452
Title: Bayesian Estimation of Inverted Beta Mixture Models With Extended Stochastic Variational Inference for Positive Vector Classification
Authors: Lai, Y
Guan, W
Luo, L
Guo, Y
Song, H
Meng, H
Keywords: extended stochastic variational inference;mixture models;Bayesian estimation;text categrization;network traffiic classification;misuse intrusion detecton
Issue Date: 25-Oct-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: Lai, 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.2022.3213518
URI: https://bura.brunel.ac.uk/handle/2438/25452
DOI: https://doi.org/10.1109/tnnls.2022.3213518
ISSN: 2162-237X
Other Identifiers: ORCID iD: Yuping Lai https://orcid.org/0000-0002-3797-1228
ORCID iD: Wenbo Guan https://orcid.org/0000-0002-4645-6121
ORCID iD: Lijuan Luo https://orcid.org/0000-0002-3702-372X
ORCID iD: Heping Song https://orcid.org/0000-0002-8583-2804
ORCID iD: Hongying Meng https://orcid.org/0000-0002-8836-1382
Appears in Collections:Dept of Electronic and Electrical Engineering Research Papers

Files in This Item:
File Description SizeFormat 
FullText.pdfCopyright © 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/23.14 MBAdobe PDFView/Open


Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.