Lower Bound of Locally Differentially Private Sparse Covariance Matrix Estimation
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[1] Úlfar Erlingsson,et al. RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response , 2014, CCS.
[2] P. Massart,et al. Adaptive estimation of a quadratic functional by model selection , 2000 .
[3] Vishesh Karwa,et al. Finite Sample Differentially Private Confidence Intervals , 2017, ITCS.
[4] Alexandre B. Tsybakov,et al. Introduction to Nonparametric Estimation , 2008, Springer series in statistics.
[5] Di Wang,et al. On Sparse Linear Regression in the Local Differential Privacy Model , 2019, IEEE Transactions on Information Theory.
[6] Feng Ruan,et al. The Right Complexity Measure in Locally Private Estimation: It is not the Fisher Information , 2018, ArXiv.
[7] Di Wang,et al. Differentially Private High Dimensional Sparse Covariance Matrix Estimation , 2019, ArXiv.
[8] Martin J. Wainwright,et al. Local privacy and statistical minimax rates , 2013, 2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton).
[9] Janardhan Kulkarni,et al. Locally Private Gaussian Estimation , 2018, NeurIPS.
[10] Mengdi Huai,et al. DIFFERENTIALLY PRIVATE SPARSE INVERSE COVARIANCE ESTIMATION , 2018, 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP).
[11] Cynthia Dwork,et al. Calibrating Noise to Sensitivity in Private Data Analysis , 2006, TCC.
[12] Harrison H. Zhou,et al. Estimating Sparse Precision Matrix: Optimal Rates of Convergence and Adaptive Estimation , 2012, 1212.2882.
[13] Harrison H. Zhou,et al. OPTIMAL RATES OF CONVERGENCE FOR SPARSE COVARIANCE MATRIX ESTIMATION , 2012, 1302.3030.
[14] Jonathan Ullman,et al. Tight Lower Bounds for Locally Differentially Private Selection , 2018, ArXiv.
[15] Joseph P. Near,et al. Differential Privacy at Scale: Uber and Berkeley Collaboration , 2018 .
[16] Yichen Wang,et al. The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy , 2019, The Annals of Statistics.
[17] Han Liu,et al. Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems , 2018, AISTATS.
[18] Martin J. Wainwright,et al. Minimax Optimal Procedures for Locally Private Estimation , 2016, ArXiv.
[19] Jon A. Wellner,et al. Weak Convergence and Empirical Processes: With Applications to Statistics , 1996 .
[20] John Duchi,et al. Lower Bounds for Locally Private Estimation via Communication Complexity , 2019, COLT.
[21] Jerry Li,et al. Privately Learning High-Dimensional Distributions , 2018, COLT.
[22] Li Zhang,et al. Analyze gauss: optimal bounds for privacy-preserving principal component analysis , 2014, STOC.
[23] Thomas Steinke,et al. Tight Lower Bounds for Differentially Private Selection , 2017, 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS).
[24] Jun Tang,et al. Privacy Loss in Apple's Implementation of Differential Privacy on MacOS 10.12 , 2017, ArXiv.
[25] Marco Gaboardi,et al. Locally Private Mean Estimation: Z-test and Tight Confidence Intervals , 2018, AISTATS.