
### Data summary
- This repository contains small synthetic data for Image datasets; MNIST, SVHN, and CIFAR-10.
- Each torch file contains the images and corresponding labels of sizes ranging from 1,10,50 images per class (IPC). 
- For more details, please refer to our GitHub page and paper below. 

### Reference
https://github.com/snu-mllab/Efficient-Dataset-Condensation

### Citation
```
@inproceedings{kimICML22,
title = {Dataset Condensation via Efficient Synthetic-Data Parameterization},
author = {Kim, Jang-Hyun and Kim, Jinuk and Oh, Seong Joon and Yun, Sangdoo and Song, Hwanjun and Jeong, Joonhyun and Ha, Jung-Woo and Song, Hyun Oh},
booktitle = {International Conference on Machine Learning (ICML)},
year = {2022}
}
```
license:mit region:us
{"license": "mit", "data_type": "image (0-1 ranged float)"}
TAGS
#license-mit #region-us 


### Data summary
- This repository contains small synthetic data for Image datasets; MNIST, SVHN, and CIFAR-10.
- Each torch file contains the images and corresponding labels of sizes ranging from 1,10,50 images per class (IPC). 
- For more details, please refer to our GitHub page and paper below. 

### Reference
URL


### Data summary
- This repository contains small synthetic data for Image datasets; MNIST, SVHN, and CIFAR-10.
- Each torch file contains the images and corresponding labels of sizes ranging from 1,10,50 images per class (IPC). 
- For more details, please refer to our GitHub page and paper below. ### Reference
URL
TAGS
#license-mit #region-us 
 ### Data summary
- This repository contains small synthetic data for Image datasets; MNIST, SVHN, and CIFAR-10.
- Each torch file contains the images and corresponding labels of sizes ranging from 1,10,50 images per class (IPC). 
- For more details, please refer to our GitHub page and paper below. ### Reference
URL
passage: TAGS
#license-mit #region-us 
### Data summary
- This repository contains small synthetic data for Image datasets; MNIST, SVHN, and CIFAR-10.
- Each torch file contains the images and corresponding labels of sizes ranging from 1,10,50 images per class (IPC). 
- For more details, please refer to our GitHub page and paper below.### Reference
URL