Dynamic Differential Privacy for ADMM-Based Distributed Classification Learning
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2016.2607691
Abstract: Privacy-preserving distributed machine learning becomes increasingly important due to the recent rapid growth of data. This paper focuses on a class of regularized empirical risk minimization machine learning problems, and develops two methods to provide… read more here.
Keywords: differential privacy; dynamic differential; variable perturbation; admm based ... See more keywords