Shuang Song

According to our database1, Shuang Song authored at least 15 papers between 2013 and 2020.

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Timeline

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Bibliography

2020
An Attack on InstaHide: Is Private Learning Possible with Instance Encoding?
CoRR, 2020

Tempered Sigmoid Activations for Deep Learning with Differential Privacy.
CoRR, 2020

Characterizing Private Clipped Gradient Descent on Convex Generalized Linear Problems.
CoRR, 2020

Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation.
CoRR, 2020

2019
That which we call private.
CoRR, 2019

2018
Privacy-Preserving Algorithms for Machine Learning.
PhD thesis, 2018

Differentially Private Continual Release of Graph Statistics.
CoRR, 2018

Scalable Private Learning with PATE.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Pufferfish Privacy Mechanisms for Correlated Data.
Proceedings of the 2017 ACM International Conference on Management of Data, 2017

Renyi Differential Privacy Mechanisms for Posterior Sampling.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Composition properties of inferential privacy for time-series data.
Proceedings of the 55th Annual Allerton Conference on Communication, 2017

2016
Privacy-preserving Analysis of Correlated Data.
CoRR, 2016

2015
Learning from Data with Heterogeneous Noise using SGD.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
The Large Margin Mechanism for Differentially Private Maximization.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
Stochastic gradient descent with differentially private updates.
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013


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