Search Results for author:
Found 2 papers, 2 papers with code
Differentially Private Synthetic Data: Applied Evaluations and Enhancements
Differentially private data synthesis protects personal details from exposure, and allows for the training of differentially private machine learning models on privately generated datasets.
Flexible and Scalable Deep Learning with MMLSpark
In this work we detail a novel open source library, called MMLSpark, that combines the flexible deep learning library Cognitive Toolkit, with the distributed computing framework Apache Spark.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
