English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

The EU General Data Protection Regulation (GDPR) mandates the principle ofdata minimization, which requires that only data necessary to fulfill a certainpurpose be collected. However, it can often be difficult to determine theminimal amount of data required, especially in complex machine learning modelssuch as neural networks. We present a first-of-a-kind method to reduce theamount of personal data needed to perform predictions with a machine learningmodel, by removing or generalizing some of the input features. Our method makesuse of the knowledge encoded within the model to produce a generalization thathas little to no impact on its accuracy. This enables the creators and users ofmachine learning models to acheive data minimization, in a provable manner.

Data Minimization for GDPR Compliance in Machine Learning Models