A golang module for differential privacy
-
Updated
Jul 15, 2020 - Go
A golang module for differential privacy
R ports of examples from Google's Differential Privacy repository.
CS6780 “Advanced Machine Learning”. Implemented multiple Federated Learning averaging methods in a Differentially Private setting and measured relative impact on model accuracy and fairness. Worked jointly with Caleb Berman of the Cornell MPS program
Bias evaluation of Differentially Private NLP models
Produces a differentially-private model for domain generation algorithm detection.
Common Data Model Project by SNUBH-SNU
Li X, Chen Y, Wang C, Shen C. When Deep Learning Meets Differential Privacy: Privacy, Security, and More. IEEE Network. 2021 Nov;35(6):148-55.
Differential private deep learning training performs well with Memorization Informed Frèchet Distance.
Python package designed to facilitate the end-to-end production of differentially private synthetic data
Code and data accompanying the DP-FSL paper
Research on federated learning and differential privacy.
A Joint Permute-and-Flip and Its Enhancement for Large-Scale Genomic Statistical Analysis
Extension for Adobe Experience Platform Data Collection Tags (Adobe Launch) to provide a simple application of differential privacy.
Repository of the Paper "Words Blending Boxes. Obfuscating Queries in Information Retrieval using Differential Privacy."
Repository for the Final Project in CSCI475 Information Security and Privacy
Local Training Node for The Sentinel AI
Differentially Private Gradient Descent Optimizers
Exploring Privacy Preserving Mechanisms for Statistical Queries in Contact Tracing Applications
Add a description, image, and links to the differential-privacy topic page so that developers can more easily learn about it.
To associate your repository with the differential-privacy topic, visit your repo's landing page and select "manage topics."