Zobrazeno 1 - 10
of 190
pro vyhledávání: '"Nissim, Kobbi"'
A firm seeks to analyze a dataset and to release the results. The dataset contains information about individual people, and the firm is subject to some regulation that forbids the release of the dataset itself. The regulation also imposes conditions
Externí odkaz:
http://arxiv.org/abs/2408.14740
Credit attribution is crucial across various fields. In academic research, proper citation acknowledges prior work and establishes original contributions. Similarly, in generative models, such as those trained on existing artworks or music, it is imp
Externí odkaz:
http://arxiv.org/abs/2406.15916
Autor:
Cohen, Edith, Kaplan, Haim, Mansour, Yishay, Moran, Shay, Nissim, Kobbi, Stemmer, Uri, Tsfadia, Eliad
We revisit the fundamental question of formally defining what constitutes a reconstruction attack. While often clear from the context, our exploration reveals that a precise definition is much more nuanced than it appears, to the extent that a single
Externí odkaz:
http://arxiv.org/abs/2405.15753
In adaptive data analysis, a mechanism gets $n$ i.i.d. samples from an unknown distribution $D$, and is required to provide accurate estimations to a sequence of adaptively chosen statistical queries with respect to $D$. Hardt and Ullman (FOCS 2014)
Externí odkaz:
http://arxiv.org/abs/2305.15452
A private learner is trained on a sample of labeled points and generates a hypothesis that can be used for predicting the labels of newly sampled points while protecting the privacy of the training set [Kasiviswannathan et al., FOCS 2008]. Research u
Externí odkaz:
http://arxiv.org/abs/2305.09579
In this work we introduce an interactive variant of joint differential privacy towards handling online processes in which existing privacy definitions seem too restrictive. We study basic properties of this definition and demonstrate that it satisfie
Externí odkaz:
http://arxiv.org/abs/2302.14099
Autor:
Beimel, Amos, Kaplan, Haim, Mansour, Yishay, Nissim, Kobbi, Saranurak, Thatchaphol, Stemmer, Uri
A dynamic algorithm against an adaptive adversary is required to be correct when the adversary chooses the next update after seeing the previous outputs of the algorithm. We obtain faster dynamic algorithms against an adaptive adversary and separatio
Externí odkaz:
http://arxiv.org/abs/2111.03980