$44
IEEE 3652.1-2020
2021
IEEE Guide for Architectural Framework and Application of Federated Machine Learning
- Format:
- Language(s) :
- Published :
- English
- 03/19/2021
New IEEE Standard – Active.
Federated machine learning defines a machine learning framework that allows a collective model to be constructed from data that is distributed across repositories owned by different organizations or devices. A blueprint for data usage and model building across organizations and devices while meeting applicable privacy, security and regulatory requirements is provided in this guide. It defines the architectural framework and application guidelines for federated machine learning, including description and definition of federated machine learning; the categories federated machine learning and the application scenarios to which each category applies; performance evaluation of federated machine learning; and associated regulatory requirements.
| IEEE 3652.1-2020 | |
|---|---|
| STANDARD INFO: | |
| Standard Name | IEEE 3652.1-2020 |
| Scope | IEEE Guide for Architectural Framework and Application of Federated Machine Learning |
| Publisher | IEEE - IEEE |
| Languages | English |
| State | |
| Publication Year | 2021 |
| Most recent Version | MOST RECENT |
| Whether to be replaced | |
| Addendum | |
| FILE INFO: | |
| File Size | 1 file , 1.9 MB |
| ISBN(s) | 9781504470537, 9781504470544 |
| Note | This product is unavailable in Russia, Ukraine, Belarus |
| Number of Pages | 69 |
| Product Code(s) | STD24407, STDPD24407 |
| Published | 03/19/2021 |
| IEEE 3652.1-2020 | ||
|---|---|---|
| History | Publisher Year | |
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