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While significant progress has been made separately on analytics systems for scalable stochastic gradient descent (SGD) and private SGD, none of the major scalable analytics frameworks have incorporated differentially private SGD.
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P. Jain, P. Kothari, and A. Thakurta · 2012
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D. Kifer, A. D. Smith, and A. Thakurta · 2012
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N. L. Roux, M. W. Schmidt, and F. R. Bach · 2012
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J. Zhang, Z. Zhang, X. Xiao, Y. Yang, and M. Winslett · 2012
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A stability-based validation procedure for differentially private machine learning
K. Chaudhuri and S. A. Vinterbo · 2013
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J. C. Duchi, M. I. Jordan, and M. J. Wainwright · 2013
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R. Bassily, A. Smith, and A. Thakurta · 2014
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C. Dwork and A. Roth · 2014
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Ú. Erlingsson, V. Pihur, and A. Korolova · 2014
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N. Parikh and S. P. Boyd · 2014
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M. Hardt, B. Recht, and Y. Singer · 2015
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Differentially private learning with kernels
P. Jain and A. Thakurta · 2013
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Accelerating stochastic gradient descent using predictive variance reduction
R. Johnson and T. Zhang · 2013
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Stochastic gradient descent with differentially private updates
S. Song, K. Chaudhuri, and A. D. Sarwate · 2013
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Privgene: differentially private model fitting using genetic algorithms
J. Zhang, X. Xiao, Y. Yang, Z. Zhang, and M. Winslett · 2013
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mahout.apache.org
Apache Mahout
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https://en.wikipedia.org/wiki/Apache˙Spark
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M. Hay, A. Machanavajjhala, G. Miklau, Y. Chen, and D. Zhang · 2015
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Deep learning with differential privacy
M. Abadi, A. Chu, I. J. Goodfellow, H. B. McMahan, I. Mironov, K. Talwar, and L. Zhang · 2016
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Without-Replacement Sampling for Stochastic Gradient Methods: Convergence Results and Application to Distributed Optimization
O. Shamir · 2016
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https://github.com/frankmcsherry/blog/blob/master/posts/2017-02-08.md
How many secrets do you have? · 2017
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