no code implementations • 21 Nov 2018 • Irene Giacomelli, Somesh Jha, Ross Kleiman, David Page, Kyonghwan Yoon
We study the problem of privacy-preserving machine learning (PPML) for ensemble methods, focusing our effort on random forests.
no code implementations • 5 Nov 2018 • Varun Chandrasekaran, Kamalika Chaudhuri, Irene Giacomelli, Somesh Jha, Songbai Yan
This has resulted in the surge of Machine Learning-as-a-Service (MLaaS) - cloud services that provide (a) tools and resources to learn the model, and (b) a user-friendly query interface to access the model.
1 code implementation • 5 Sep 2017 • Samuel Yeom, Irene Giacomelli, Matt Fredrikson, Somesh Jha
This paper examines the effect that overfitting and influence have on the ability of an attacker to learn information about the training data from machine learning models, either through training set membership inference or attribute inference attacks.