Fetching the paper…
Reading the bibliography…
The wide deployment of machine learning in recent years gives rise to a great demand for large-scale and high-dimensional data, for which the privacy raises serious concern.
Calibrating noise to sensitivity in private data analysis
Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith · 2006
Earlier work this paper cites.
Learning word vectors for sentiment analysis
Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts · 2011
Earlier work this paper cites.
Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds
Raef Bassily, Adam Smith, and Abhradeep Thakurta · 2014
Earlier work this paper cites.
The algorithmic foundations of differential privacy
Cynthia Dwork, Aaron Roth, et al · 2014
Earlier work this paper cites.
The matrix mechanism: optimizing linear counting queries under differential privacy
Chao Li, Gerome Miklau, Michael Hay, Andrew McGregor, and Vibhor Rastogi · 2015
Earlier work this paper cites.
Deep Learning with Differential Privacy
Martin Abadi, Andy Chu, Ian Goodfellow, H Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang · 2016
Cited alongside, same era.
Concentrated differential privacy
Cynthia Dwork and Guy N Rothblum · 2016
Cited alongside, same era.
Uci machine learning repository, 2017
Dheeru Dua and Casey Graff · 2017
Cited alongside, same era.
The Composition Theorem for Differential Privacy
Peter Kairouz, Sewoong Oh, and Pramod Viswanath · 2017
Cited alongside, same era.
Rényi differential privacy
Ilya Mironov · 2017
Later among the works it cites.
Improving the gaussian mechanism for differential privacy: Analytical calibration and optimal denoising
Borja Balle and Yu-Xiang Wang · 2018
Later among the works it cites.
Mvg mechanism: Differential privacy under matrix-valued query
Thee Chanyaswad, Alex Dytso, H Vincent Poor, and Prateek Mittal · 2018
Later among the works it cites.
Optimizing error of high-dimensional statistical queries under differential privacy
Ryan McKenna, Gerome Miklau, Michael Hay, and Ashwin Machanavajjhala · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…