[R] SGD on Random Mixtures (SGDRM): Private Machine Learning under Data Breach Threats • r/MachineLearning

We share our new paper on Stochastic Gradient Descent on Random Mixtures (SGDRM), which is a simple way of protecting data under data breach threats. The key idea of SGDRM is simple: we run SGD algorithm on random mixtures of the training data points. With SGDRM, when a data breach occurs, only the random mixtures will be leaked, not the original dataset! The detailed mechanism of SGDRM is summarized in the figure. We experimentally observe that SGDRM performs pretty well on general deep learning tasks such as MNIST/CIFAR10/Skin-Lesion classification.