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Working under a model of privacy in which data remains private even from the statistician, we study the tradeoff between privacy guarantees and the risk of the resulting statistical estimators.
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C. Dwork, F. McSherry, K. Nissim, and A. Smith · 2006
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A unified framework for high-dimensional analysis of M {M} -estimators with decomposable regularizers
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Robust stochastic approximation approach to stochastic programming
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C. Dwork, G. N. Rothblum, and S. P. Vadhan · 2010
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S. E. Fienberg, A. Rinaldo, and X. Yang · 2010
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S. Negahban, P. Ravikumar, M. Wainwright, and B. Yu · 2012
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Learning in a large function space: privacy-preserving mechanisms for SVM learning
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How censorship in China allows government criticism but silences collective expression
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J. C. Duchi, M. I. Jordan, and M. J. Wainwright · 2014
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P. Kairouz, S. Oh, and P. Vishwanath · 2014
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2010 annual report on employee compensation, 2014
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