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Exponential mechanism (differential privacy) : ウィキペディア英語版 | Exponential mechanism (differential privacy) The exponential mechanism is a technique for designing differentially private algorithms developed by (Frank McSherry ) and (Kunal Talwar ). Differential privacy is a technique for releasing statistical information about a database without revealing information about its individual entries. Most of the initial research in the field of differential privacy revolved around real valued functions which have relatively low sensitivity to change in the data of a single individual and whose usefulness is not hampered by small additive perturbations. A natural question is what happens in the situation when one wants to preserve more general sets of properties. The Exponential Mechanism helps to extend the notion of differential privacy to address these issues. Moreover, it describes a class of mechanisms that includes all possible differentially private mechanisms. == The exponential mechanism 〔(F.McSherry and K.Talwar. Mechasim Design via Differential Privacy. Proceedings of the 48th Annual Symposium of Foundations of Computer Science, 2007. )〕 ==
抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)』 ■ウィキペディアで「Exponential mechanism (differential privacy)」の詳細全文を読む
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