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pro vyhledávání: '"Deng, Zirui"'
Delegating large-scale computations to service providers is a common practice which raises privacy concerns. This paper studies information-theoretic privacy-preserving delegation of data to a service provider, who may further delegate the computatio
Externí odkaz:
http://arxiv.org/abs/2405.05567
A typical setup in many machine learning scenarios involves a server that holds a model and a user that possesses data, and the challenge is to perform inference while safeguarding the privacy of both parties. Private Inference has been extensively e
Externí odkaz:
http://arxiv.org/abs/2311.13686
Autor:
Deng, Zirui, Raviv, Netanel
Private inference refers to a two-party setting in which one has a model (e.g., a linear classifier), the other has data, and the model is to be applied over the data while safeguarding the privacy of both parties. In particular, models in which the
Externí odkaz:
http://arxiv.org/abs/2305.03801