8 datasets found

PrivEdge: From Local to Distributed Private Training and Prediction

The dataset used in the paper is a set of consumer and producer utilities pairs that can be achieved by market segmentations under privacy constraints.

The dataset contains 92 pairs of multi-labeled privacy-related questions from Stack Overflow.

The dataset contains news articles from French, German, UK, and US sources about GDPR media discourse.

The authors used the UCI Bank Marketing Dataset (UBMD), Lesion Disease Classification (LDC) and CIFAR-10 datasets for their experiments.

The SPHP dataset contains synchronized, complementary images of edge and motion vectors along with ground truth labels for 13 joints.

The proposed double-private algorithm combines differential privacy and cryptography to enhance privacy in distributed estimation.

This dataset contains Flickr images on various subjects, which are manually labeled as public or private by external viewers.