A golang module for differential privacy
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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.
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
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
Repository for the Final Project in CSCI475 Information Security and Privacy
Local Training Node for The Sentinel AI
Differentially Private Gradient Descent Optimizers. DA204 Course Project
Exploring Privacy Preserving Mechanisms for Statistical Queries in Contact Tracing Applications
Implementation of DPRL
Assessing the Impact of Differential Privacy on Population Uniques in Geographically Aggregated Data: The Case of the 2020 U.S. Census
In this project we add differential privacy into an openset recognizer.to implement DP we use opacus library.
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