Data · dataset · 2022

ICML2022/EfficientDatasetCondensation

Listed in Hugging Face Datasets

Data summary This repository contains small synthetic data for Image datasets; MNIST, SVHN, and CIFAR-10.

Description

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 github.com/snu-mllab/Efficient-Dataset-Condensation Citation @inproceedings{kimICML22, title = {Dataset Condensation via Efficient Synthetic-Data… See the full description on the dataset page: huggingface.co/datasets/ICML2022/EfficientDatasetCondensation.

Topics

From keywords: Computer Science & AI
Inferred from text: Image 75%

Provenance · 1 source records, 9 field assertions

Source	Key	Last seen	Raw
Hugging Face Datasets	ICML2022/EfficientDatasetCondensation	15 d ago	JSON v1

Field	Assertion	Extractor	Evidence
access_level	source · Hugging Face	connector:huggingface@1.0.0	/gated
concepts[field].local:field:computer-science-ai	mapping · Hugging Face	connector:huggingface@1.0.0
concepts[modality].local:modality:image	enrichment · Hugging Face	keyword-concept-rules@1.0.0	title+description (75%)
created_date	source · Hugging Face	connector:huggingface@1.0.0
description	source · Hugging Face	connector:huggingface@1.0.0	/description
license	source · Hugging Face	connector:huggingface@1.0.0	/tags[license:*]
publication_date	source · Hugging Face	connector:huggingface@1.0.0
title	source · Hugging Face	connector:huggingface@1.0.0	/id
updated_date	source · Hugging Face	connector:huggingface@1.0.0

ICML2022/EfficientDatasetCondensation

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