| dc.contributor.author | Koda, Yusuke | |
| dc.contributor.author | Park, Jihong | |
| dc.contributor.author | Bennis, Mehdi | |
| dc.contributor.author | Vepakomma, Praneeth | |
| dc.contributor.author | Raskar, Ramesh | |
| dc.date.accessioned | 2022-11-17T18:22:40Z | |
| dc.date.available | 2022-11-17T18:22:40Z | |
| dc.date.issued | 2021 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/146533 | |
| dc.language.iso | en | |
| dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
| dc.relation.isversionof | 10.1109/GLOBECOM46510.2021.9685232 | en_US |
| dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | en_US |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en_US |
| dc.source | arXiv | en_US |
| dc.title | AirMixML: Over-the-Air Data Mixup for Inherently Privacy-Preserving Edge Machine Learning | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Koda, Yusuke, Park, Jihong, Bennis, Mehdi, Vepakomma, Praneeth and Raskar, Ramesh. 2021. "AirMixML: Over-the-Air Data Mixup for Inherently Privacy-Preserving Edge Machine Learning." 2021 IEEE Global Communications Conference (GLOBECOM). | |
| dc.contributor.department | Program in Media Arts and Sciences (Massachusetts Institute of Technology) | en_US |
| dc.relation.journal | 2021 IEEE Global Communications Conference (GLOBECOM) | en_US |
| dc.eprint.version | Author's final manuscript | en_US |
| dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
| eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
| dc.date.updated | 2022-11-17T18:18:48Z | |
| dspace.orderedauthors | Koda, Y; Park, J; Bennis, M; Vepakomma, P; Raskar, R | en_US |
| dspace.date.submission | 2022-11-17T18:18:50Z | |
| mit.license | OPEN_ACCESS_POLICY | |
| mit.metadata.status | Authority Work and Publication Information Needed | en_US |
