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We propose a numerical accountant for evaluating the tight $(\varepsilon,\delta)$-privacy loss for algorithms with discrete one dimensional output.
Rényi differential privacy of the sampled Gaussian mechanism
Mironov, I., Talwar, K., and Zhang, L. (2019) · 1908
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Advances and open problems in federated learning
Kairouz, P., McMahan, H. B., Avent, B., Bellet, A., Bennis, M., Bhagoji, A. N., Bonawitz, K., Charles, Z., Cormode, G., Cummings, R., et al. (2019) · 1912
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An algorithm for the machine calculation of complex Fourier series
Cooley, J. W. and Tukey, J. W. (1965) · 1965
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Randomized response: A survey technique for eliminating evasive answer bias
Warner, S. L. (1965) · 1965
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High-speed convolution and correlation
Stockham Jr, T. G. (1966) · 1966
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Calibrating noise to sensitivity in private data analysis
Dwork, C., McSherry, F., Nissim, K., and Smith, A. (2006) · 2006
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On significance of the least significant bits for differential privacy
Mironov, I. (2012) · 2012
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Beyond differential privacy: composition theorems and relational logic for f-divergences between probabilistic programs
Barthe, G. and Olmedo, F. (2013) · 2013
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Introduction to numerical analysis
Stoer, J. and Bulirsch, R. (2013) · 2013
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The algorithmic foundations of differential privacy
Dwork, C. and Roth, A. (2014) · 2014
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Deep learning with differential privacy
Abadi, M., Chu, A., Goodfellow, I., McMahan, H. B., Mironov, I., Talwar, K., and Zhang, L. (2016) · 2016
Cited alongside, same era.
Rényi differential privacy
Mironov, I. (2017) · 2017
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cpSGD: Communication-efficient and differentially-private distributed SGD
Agarwal, N., Suresh, A. T., Yu, F. X. X., Kumar, S., and McMahan, B. (2018) · 2018
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Privacy amplification by subsampling: Tight analyses via couplings and divergences
Balle, B., Barthe, G., and Gaboardi, M. (2018) · 2018
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Tight on budget?: Tight bounds for r-fold approximate differential privacy
Meiser, S. and Mohammadi, E. (2018) · 2018
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Privacy loss classes: The central limit theorem in differential privacy
Sommer, D. M., Meiser, S., and Mohammadi, E. (2019) · 2019
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High-dimensional statistics: A non-asymptotic viewpoint
Wainwright, M. J. (2019) · 2019
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Subsampled Rényi differential privacy and analytical moments accountant
Wang, Y.-X., Balle, B., and Kasiviswanathan, S. P. (2019) · 2019
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Poisson subsampled Rényi differential privacy
Zhu, Y. and Wang, Y.-X. (2019) · 2019
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Optimal differential privacy composition for exponential mechanisms
Dong, J., Durfee, D., and Rogers, R. (2020) · 2020
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Improving the gaussian mechanism for differential privacy: Analytical calibration and optimal denoising
Balle, B. and Wang, Y.-X. (2018) · 2018
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Computing tight differential privacy guarantees using FFT
Koskela, A., Jälkö, J., and Honkela, A. (2020) · 2020
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