Datasetpublic

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… See the full description on the dataset page: https://huggingface.co/datasets/ICML2022/EfficientDatasetCondensation.

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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}
}