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http://bura.brunel.ac.uk/handle/2438/31733Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Zhang, Y | - |
| dc.contributor.author | Zhang, G | - |
| dc.contributor.author | Yang, K | - |
| dc.contributor.author | Wen, Y | - |
| dc.contributor.author | Wang, K | - |
| dc.date.accessioned | 2025-08-12T16:41:10Z | - |
| dc.date.available | 2025-08-12T16:41:10Z | - |
| dc.date.issued | 2025-06-24 | - |
| dc.identifier | ORCiD: Yue Zhang https://orcid.org/0009-0006-3215-9464 | - |
| dc.identifier | ORCiD: Guopeng Zhang https://orcid.org/0000-0001-7524-3144 | - |
| dc.identifier | ORCiD: Kun Yang https://orcid.org/0000-0002-6782-6689 | - |
| dc.identifier | ORCiD: Yao Wen https://orcid.org/0000-0002-5182-5999 | - |
| dc.identifier | ORCiD: Kezhi Wang https://orcid.org/0000-0001-8602-0800 | - |
| dc.identifier.citation | Zhang, Y. et al. (2025) 'Enhancing Collaborative Machine Learning in Resource-Limited Networks through Knowledge Distillation and Over-the-Air Computation', IEEE Transactions on Mobile Computing, 24 (11), pp. 12177 - 12192. doi: 10.1109/TMC.2025.3582683. | - |
| dc.identifier.issn | 1536-1233 | - |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/31733 | - |
| dc.description.sponsorship | Postgraduate Research and Practice Innovation Program of Jiangsu Province (Grant Number: KYCX25_2894); 10.13039/501100012226-Fundamental Research Funds for the Central Universities (Grant Number: 2025-00063); Graduate Innovation Program of China University of Mining and Technology (Grant Number: 2025WLKXJ208); Jiangsu Major Project on Basic Researches (Grant Number: BK20243059); Gusu Innovation Project for People (Grant Number: ZXL2024360); 10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62132004). | - |
| dc.format.extent | 12177 - 12192 | - |
| dc.format.medium | Print-Electronic | - |
| dc.language | English | - |
| dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | - |
| dc.rights | Copyright © 2025 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 ( https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelines-and-policies/post-publication-policies/ ). | - |
| dc.rights.uri | https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelines-and-policies/post-publication-policies/ | - |
| dc.title | Enhancing Collaborative Machine Learning in Resource-Limited Networks through Knowledge Distillation and Over-the-Air Computation | - |
| dc.type | Journal Article | - |
| dc.identifier.doi | https://doi.org/10.1109/TMC.2025.3582683 | - |
| dc.relation.isPartOf | IEEE Transactions on Mobile Computing | - |
| pubs.issue | 11 | - |
| pubs.publication-status | Published | - |
| pubs.volume | 24 | - |
| dc.identifier.eissn | 1558-0660 | - |
| dc.rights.holder | Institute of Electrical and Electronics Engineers (IEEE) | - |
| Appears in Collections: | Dept of Computer Science Research Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | Copyright © 2025 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 ( https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelines-and-policies/post-publication-policies/ ). | 2.43 MB | Adobe PDF | View/Open |
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