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dc.contributor.authorHu, Lijie
dc.contributor.authorNi, Shuo
dc.contributor.authorXiao, Hanshen
dc.contributor.authorWang, Di
dc.date.accessioned2022-11-15T18:48:17Z
dc.date.available2022-11-15T18:48:17Z
dc.date.issued2022-06-12
dc.identifier.isbn978-1-4503-9260-0
dc.identifier.urihttps://hdl.handle.net/1721.1/146475
dc.publisherACM|Proceedings of the 41st ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systemsen_US
dc.relation.isversionofhttps://doi.org/10.1145/3517804.3524144en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceACM|Proceedings of the 41st ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systemsen_US
dc.titleHigh Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Dataen_US
dc.typeArticleen_US
dc.identifier.citationHu, Lijie, Ni, Shuo, Xiao, Hanshen and Wang, Di. 2022. "High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data."
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.identifier.mitlicensePUBLISHER_POLICY
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2022-11-03T12:30:12Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2022-11-03T12:30:12Z
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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