Applying Differentially Private Stochastic Gradient Descent (DPSGD) to
t...
We study Gaussian mechanism in the shuffle model of differential privacy...
Local differential privacy (LDP) gives a strong privacy guarantee to be ...
Recent studies of distributed computation with formal privacy guarantees...
Recently, it is shown that shuffling can amplify the central differentia...
How can we explore the unknown properties of high-dimensional sensitive
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We propose a new framework of synthesizing data using deep generative mo...
Transfer learning is a useful machine learning framework that allows one...
How can we release a massive volume of sensitive data while mitigating
p...
This paper studies how to learn variational autoencoders with a variety ...
Graph convolutional neural networks, which learn aggregations over neigh...
We study locally differentially private algorithms for reinforcement lea...
How can we make machine learning provably robust against adversarial exa...