A benchmark for proximity-based non-IID Federated Learning
Project description
ProFed: A Benchmark for Proximity-based Federated Learning
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
profed-0.6.3.tar.gz
(4.1 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file profed-0.6.3.tar.gz.
File metadata
- Download URL: profed-0.6.3.tar.gz
- Upload date:
- Size: 4.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.8.3 CPython/3.12.10 Linux/6.11.0-1015-azure
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
446de112daa397c4e667232dfc172eaf511c02bf1521ea452dd59aae155f7073
|
|
| MD5 |
4002d8d23f5f12f7f1d7312702a2d9aa
|
|
| BLAKE2b-256 |
631f2b85d35ce9e1abd96745d999d48bebba8ce4a0fa9d33254661379db1d9bf
|
File details
Details for the file profed-0.6.3-py3-none-any.whl.
File metadata
- Download URL: profed-0.6.3-py3-none-any.whl
- Upload date:
- Size: 5.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.8.3 CPython/3.12.10 Linux/6.11.0-1015-azure
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
13c57899e26be5137257b38bf4c8f714598e718af69c87c86922a760a4541891
|
|
| MD5 |
0fd272221dd5e79beca0ea7fc6f8eb1b
|
|
| BLAKE2b-256 |
3480dc0c56c0af6782c2765a787ddf7d62d3b541175bdf67b865965829d6f5e6
|
