Email: shs037 at eng dot ucsd dot edu
I am currently a 6th year PhD student in UC San Diego. I am working with Prof. Kamalika Chaudhuri in Machine Learning and Differential Privacy. Before joining UCSD, I obtained my BSc degree in Mathematics and Computer Science from The Hong Kong University of Science and Technology.
I was an intern in the Google Brain Team during Summer 2017.
Scalable Private Learning with PATE [pdf]
Nicolas Papernot, Shuang Song, Ilya Mironov, Ananth Raghunathan, Kunal Talwar and Ulfar Erlingsson, International Conference on Learning Representations (ICLR), 2018
Rényi Differential Privacy Mechanisms for Posterior Sampling [pdf]
Joseph Geumlek, Shuang Song and Kamalika Chaudhuri, Neural Information Processing Systems (NIPS), 2017
Composition Properties of Inferential Privacy for Time-Series Data [pdf]
Shuang Song and Kamalika Chaudhuri, Allerton Conference on Communication, Control and Computing, 2017
Learning from Data with Heterogenous Noise using SGD [pdf]
Shuang Song, Kamalika Chaudhuri and Anand D. Sarwate, International Conference on Artificial Intelligence and Statistics (AISTATS) 2015
The Large Margin Mechanism for Differentially Private Maximization [pdf]
Kamalika Chaudhuri, Daniel Hsu and Shuang Song, Neural Information Processing Systems (NIPS) 2014
Stochastic Gradient Descent with Differentially Private Updates [pdf]
Shuang Song, Kamalika Chaudhuri and Anand Sarwate, GlobalSIP Conference, 2013