Produces a differentially-private model for domain generation algorithm detection.
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Updated
Jan 15, 2024 - Jupyter Notebook
Produces a differentially-private model for domain generation algorithm detection.
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
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."
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
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