Private Learning Implies Online Learning: An Efficient Reduction
Author(s): Gonen, Alon; Hazan, Elad; Moran, Shay
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Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Gonen, Alon | - |
dc.contributor.author | Hazan, Elad | - |
dc.contributor.author | Moran, Shay | - |
dc.date.accessioned | 2021-10-08T19:49:50Z | - |
dc.date.available | 2021-10-08T19:49:50Z | - |
dc.date.issued | 2019 | en_US |
dc.identifier.citation | Gonen, Alon, Elad Hazan, and Shay Moran. "Private Learning Implies Online Learning: An Efficient Reduction." Advances in Neural Information Processing Systems 32 (2019). | en_US |
dc.identifier.issn | 1049-5258 | - |
dc.identifier.uri | https://papers.nips.cc/paper/2019/file/700fdb2ba62d4554dc268c65add4b16e-Paper.pdf | - |
dc.identifier.uri | http://arks.princeton.edu/ark:/88435/pr1nk14 | - |
dc.description.abstract | We study the relationship between the notions of differentially private learning and online learning. Several recent works have shown that differentially private learning implies online learning, but an open problem of Neel, Roth, and Wu \cite{NeelAaronRoth2018} asks whether this implication is {\it efficient}. Specifically, does an efficient differentially private learner imply an efficient online learner? In this paper we resolve this open question in the context of pure differential privacy. We derive an efficient black-box reduction from differentially private learning to online learning from expert advice. | en_US |
dc.language.iso | en_US | en_US |
dc.relation.ispartof | Advances in Neural Information Processing Systems | en_US |
dc.rights | Final published version. Article is made available in OAR by the publisher's permission or policy. | en_US |
dc.title | Private Learning Implies Online Learning: An Efficient Reduction | en_US |
dc.type | Conference Article | en_US |
pu.type.symplectic | http://www.symplectic.co.uk/publications/atom-terms/1.0/conference-proceeding | en_US |
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File | Description | Size | Format | |
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PrivateLearningOnlineLearning.pdf | 261.43 kB | Adobe PDF | View/Download |
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