Rezultati

eNauka >  Results >  Differentially Private Synthetic Data with Private Density Estimation
Title: Differentially Private Synthetic Data with Private Density Estimation
Authors: Bojkovic, Nikolija; Loh, Po Ling
Issue Date: 2024
Publication: 2024 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY, ISIT 2024
ISSN: 2157-8095 Search Idenfier
Type: Conference Paper
Collation: str. 599-604
DOI: 10.1109/ISIT57864.2024.10619641
WoS-ID: 001304426900102
Scopus-ID: 2-s2.0-85202870558
URI: https://enauka.gov.rs/handle/123456789/973056
Project: Cantab Capital Institute for the Mathematics of Information via the Philippa Fawcett Internship programme (Faculty of Mathematics, University of Cambridge)
Metadata source: (Preuzeto iz Nasi u WoS)
M-category: 
Mp. category will be shown later

Alt metrika
Dimensions
Unpaywall

Google ScholarTM

Rezultati na eNauka su zaštićeni autorskim pravima i sva prava su zadržana, osim ako nije drugačije naznačeno.