A scheme for privacy-preserving learning on Tiny Devices.
-
Updated
Jan 12, 2022 - C++
A scheme for privacy-preserving learning on Tiny Devices.
This repository contains the spreadsheet of the quantitative analysis performed for the paper "Suitability of Forward-Forward and PEPITA Learning to MLCommons-Tiny benchmarks".
Add a description, image, and links to the tiny-devices topic page so that developers can more easily learn about it.
To associate your repository with the tiny-devices topic, visit your repo's landing page and select "manage topics."