# LEAF_prepartitioned

**Repository Path**: wingter/LEAF_prepartitioned

## Basic Information

- **Project Name**: LEAF_prepartitioned
- **Description**: Pre-partitioned, small-scaled datasets from LEAF (https://leaf.cmu.edu/), NIST and CIFAR for FL research
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2026-04-29
- **Last Updated**: 2026-04-29

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# FL data prepartitioned
Pre-partitioned small-scale datasets from public repositories (including [LEAF](https://leaf.cmu.edu/), [NIST](https://www.nist.gov/itl/products-and-services/emnist-dataset), [CIFAR](https://www.cs.toronto.edu/~kriz/cifar.html), etc.) for FL research.

Pre-partitioned data are provided along with demo codes for data loading with PyTorch.

Copyrights of the data are owned by the creators. 

**Source data**: 
- LEAF GitHub repo (https://github.com/TalwalkarLab/leaf/tree/master/data)
- EMNIST (https://www.nist.gov/itl/products-and-services/emnist-dataset)
- CIFAR-10/100 (https://www.cs.toronto.edu/~kriz/cifar.html)

Please cite these papers when using the corresponding data whenever possible:
- [S. Caldas et al., LEAF: A Benchmark for Federated Settings](https://arxiv.org/pdf/1812.01097.pdf)
- [G. Cohen et al., EMNIST: an extension of MNIST to handwritten letters](https://arxiv.org/abs/1702.05373v1)
- [A. Krizhevsky, Learning Multiple Layers of Features from Tiny Images](https://www.cs.toronto.edu/~kriz/learning-features-2009-TR.pdf)