ICML2022/EfficientDatasetCondensation

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}
}